[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Триває набір до лав «Гвардії наступу»: охочі приєднатися – робіть свій вибір уже сьогодні. Залишилося лише 2 тижні, щоб зробити свій остаточний вибір на користь боротьби та свободи.
Нагадуємо, Гвардія наступу – це вісім штурмових бригад МВС України, шість з яких створюються в складі Національної гвардії України й по одній бригаді – в складі Національної поліції та Державної прикордонної служби.
Призначення новостворених бригад – остаточне звільнення окупованих територій нашої держави від російських загарбників.
Найкращі серед найбільш мотивованих уже тренуються, команда Гвардії наступу щодня більшає і стає сильнішою. Не втрачайте свій шанс приєднатися до тих, хто звільнить Україну. Долучайся до Гвардії наступу!
Джерело: сайт МВС
https://youtu.be/20eFBp5xNow


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
ПЕТРУШЕВСЬКИЙ
 pinned «
Як же приємно дивитися на те, що в пропагандистів бомбить пукан через диверсантів в Криму.  Але найсмішніше це новий фейк про Олену Зеленську. Дивіться і посміхайтеся разом з нами  https://youtu.be/7DVZu8MiJKI?si=4-4MyQoLHyIyKmDr
»


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
В Одессе хотят переименовать площадь Льва Толстого.
Об этом сообщил сайт Одесского горсовета.
"Площадь Льва Толстого, который не связан с Одессой, предложено назвать в честь одного из основоположников еврейской литературы на языке идиш Менделя Мойхер-Сфроима (умер в Одессе в 1917 году).
Перед окончательным переименованием будут проведены консультации с филологами и еврейской общиной относительно корректной формулировки названия", - отметили в мэрии.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
- Идет массовое нагнетание по поводу масштабного наступления «вот-вот».
В том числе, якобы из Беларуси - на запад Украины.
Кремль работает системно, но тупо, спалив изрядное количество своих говорящих голов.)
Очень многие люди дружно сглатывают страшилки про «большую войну», а главное - они делают это с удовольствием, ибо для массовой коммуникации расчёт на эмоции эффективнее, чем на рацио.
Предлагаю моей аудитории через недельку самостоятельно проанализировать кто, как и когда разгонял фейк про «всёпропало уже 15-18 января».
И если Вы думаете, что среди таких - только «простые люди», вы сильно ошибаетесь.
Всю войну «страшное наступление из Беларуси» пересылалось, пересылается и, увы, будет пересылаться в чатах весьма ответственных «керівників».


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Дівчині з Дніпра, за порятунком якої спостерігав увесь світ – 23 роки, лише кілька місяців тому вона втратила на війні кохану людину.
Тепер ворожа ракета зруйнувала її будинок, а доля батьків, які опинилися під завалами, наразі невідома.
✅
@ny_i_dnipro


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Если всерьез встанет
вопрос о существовании России
, то он будет решен не на украинском фронте, а вместе с вопросом дальнейшего
существования всей человеческой цивилизации
, двусмысленностей здесь быть не должно - "
мир без России нам не нужен
", заявил замруководителя российского Совбеза Медведев.
В статье для "Известий" Медведев отметил, что враги России продолжают "накачивать оружием неофашистский киевский режим и препятствовать любой возможности возродить переговоры", не желая понять, что их цели заведомо ведут к проигрышу для всех, "когда о прежней жизни придется забыть на века, пока не перестанут исходить радиацией дымные завалы".
По его словам, "спокойная мощь нашей большой страны и авторитет ее партнеров - залог сохранения будущего для всего нашего Мира". У Запада сохраняются иллюзии, что они смогут без проблем для себя похоронить Россию, но как с СССР не получится, уверен Медведев.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Непродовження «зернової угоди» дорого коштуватиме росії, – Салліван
Якщо вони справді вийдуть з цієї угоди, решта світу подивиться на це і скаже, що росія відвернулася від забезпечення того, щоб країни Глобального Півдня, Африки, Латинської Америки та Азії могли отримати продовольство, якого вони потребують за доступними цінами. І я думаю, що надалі це призведе до величезних дипломатичних витрат для росії. Тож путіну доведеться зробити вибір», - заявив радник Президента США з питань національної безпеки Джейкоб Салліван.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
📩

Видимо стартует новый проект вымывания денег из бюджета, затмевающий даже Велике Будивництво.
Теперь все под грифом "секретно" - миллионы тонн стали и кубометров бетона, десятки тысяч людей в блиндажах на годы....
Вот чисто любопытно, наверное все-таки "дешевле" остановиться, подписать М-3 и начать отстраивать страну?
...но видимо это все не про этих вороватых п@дарасов.
PS и да, чьи же решения и действия мы по итогу назовем "геноцидом" украинского народа?
Геноцидом мы назовём в учебниках ровно то, что будет выгодно

следующей концептуальной власти в Украине.
Помните, что неудачный переворот - мятеж, а удачный - революция
🤷
Так и с геноцидом будет. Что скажут назвать, то и назовём официально, а дома, на кухне, называйте, что хотите. Так устроен мир


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
🥷
Отже, влітаємо всі на ЗБІІІІІІІР.
Збираємо на авто для тих, чиї операції увійдуть до підручників. Для тих, кого називати ми, на жаль, не можемо((
Пацани ходять по тилам підорів, та трахають їх там в дупу
🤫
До речі, з крайнього виходу вони привезли купу ніштяків. Такого ви ще не бачили ніде, їх ми в наступному місяці розіграємо)
🎯
Зібрано: 370 000грн
🐈
Кожен котик зможе прийняти учась у розіграші тубусу, якщо скине 150грн і більше))
ХОЧ ГРИВНЮ, АЛЕ КОЖЕН!!
Маленьких донатів не буває)
Звіти, як завжди,
тут
Збір закрито
‼


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Зруйнований РФ стадіон у Чернігові відбудують за 700 млн грн.
 Кошти на відновлення буде виділено з державного бюджету.
За словами голови департаменту спорту Чернігівської ОДА Андрія Шемеця, зруйновані будівлі спорткомплексу будуть здебільшого розібрані, на його місці буде відбудовано новий стадіон, який відповідає всім сучасним вимогам. За прогнозами, його
будівництво може тривати до чотирьох років
.
ОЙ, ЯКА ГАРНА ШТУКА - БУДУВАТИ СТАДІОНИ. ТА ЩЕ Й ЧОТИРИ РОКИ. ДАЙ БОГ, ЩОБ 700 ЛЯМІВ ЗА ЦЕЙ ПЕРІОД НЕ ПЕРЕТВОРИЛИСЬ НА 2-3 МІЛЬЯРДА ТА НА КІЛЬКА ОБ'ЄКТІВ ЗАКОРДОННОЇ НЕРУХОМОСТІ ПРИЧЕТНИХ ДО ВІДНОВЛЕННЯ.
БАЧИТЕ, ЯКА ЛАЖА - НАВІТЬ МОЖЛИВО ГАРНІ НАМІРИ ЧИНОВНИКІВ ВИКЛИКАЮТЬ НЕДОВІРУ. СОРРІ - ЧИНОВНИКИ САМІ НАС ЗМУСИЛИ НЕДОВІРЯТИ.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Если
Путин
будет избран на ещё один 6-летний, он
 превзойдет Сталина,
который руководил Советским Союзом с 1924 по 1953 год и
 станет самым долго правящим главой российского государства
 со времен императрицы Екатерины Великой в XVIII веке, —
Der Spiegel
Подписаться на Инсайдер
 |
Прислать контент


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
❗
Французский телеканал LCI утверждает, что Польша и страны Балтии готовятся ввести свои войска на Украину
По данным телеканала,«анонимные источники в правительстве Польши сообщают, что сейчас поляки ждут окончательного результата украинского контрнаступления и наступательных действий российских войск.
Если выяснится, что Россия выигрывает войну на Украине, поляки могут ввести в этом году первую дивизию, в которую войдут поляки, прибалты, некоторое количество украинцев».


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User] Затаив дыхание наблюдаю, как Евгений Пригожин разносит систему, которая была создана на исключительной трусости, лизоблюдстве и нерешительности. Оказывается, вся эта огромная махина могла бороться только со студентами-блогерами, толстовцами, непротивлением злу, матерями-одиночками и пенсионерами из городских сумасшедших и наивных мечтателей, из разряда «пусть будет хорошо всем хорошим и плохо всем плохим, но так чтобы ещё лавочки были красивые». С ними товарищ майор расправлялся безжалостно долго, поочереди перемалывая тех, кто и сами были не прочь залезть в мясорубку и считали это буквально своей гражданской доблестью – гордо и самостоятельно пройти в автозак. Но вдруг наглый мужчина, понявший, что терять ему уже в принципе нечего, решил проверить, а чем система может ответить на вопрос «да, я с автоматом, и хули ты мне сделаешь?». И система просто сломалась, потому что с таким вопросом она не сталкивалась никогда. Как посадить пенсионера за пост ВКонтакте – система знает, а что делать, когда ей говорят «эй, чмо, я тебя к стенке вместе с твоим министром поставлю» - система не знает, а поскольку она выстроена на страхе и покорности, то жмется к стенке интуитивно, чуть ли ни на рефлексе. Просто и упоительно


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Що ж, передстанній пост у 2023.
Хочу востаннє в цьому році запросити вас долучитись до допомоги Силам Оборони, нашій опорі, людям з великої літери, Українському Війську.
Оборонці Авдіївки, тієї самої, з найгарячішого місця на планеті, звернулися з проханням в купівлі дрона Mavic 3T і планшет Samsung Galaxy Tab Active4 Pro 10.1 GB.
Давайте усі разом, без вийнятку, віддячимо ЗСУ, завдяки яким зустрічаємо прийдешній 2024 з близькими в цей святковий вечір.
Зараз у вас є змога зробити подарунок під ялинку хлопцям, які тримають Авдіївку. Приєднуйтесь всі до святково збору. Давайте створимо нову традицію — донат, замість олівʼє.
❗
ЗБІР ЗАКРИТО


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
#сплетни

Пошли сплетни, что моральный дух ВСУ из-за тотальной беспредельной мобилизации упал на самые низкие показатели.
Офис Президента хочет ввести в армии даже специальный отдел «психологического наставления», чтобы мотивировать бойцов, но это сложный процесс и на это нет не денег не кадров.
Из-за этого Банковая не проводит широкое наступление, а сфокусированы на точечных спецопераций.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
10 фактов о пособии на ребенка до 3 лет из средств материнского капитала
1⃣
 С 2023 года пособие можно оформить на любого ребенка до 3 лет в семье независимо от очередности рождения (раньше такие выплаты можно было оформить только на второго ребенка).
2⃣
 Если в семье несколько детей до 3 лет, то пособие можно оформить на каждого из них.
3⃣
 Получать выплату могут семьи со среднедушевым доходом не выше 2 прожиточных минимумов в регионе на человека.
4⃣
 Расчетный период, за который проверяют доходы семьи, — 12 месяцев, предшествующих 1 месяцу до подачи заявления.
5⃣
 При назначении не применяется комплексная оценка нуждаемости — не учитываются имущество семьи и «правило нулевого дохода».
6⃣
 С 2023 года выплата назначается на 12 месяцев,  но не более чем до трехлетия ребенка (ранее пособие назначалось до года, двух и трех лет ребенка).
7⃣
 Выплачивается за полный месяц независимо от даты рождения ребенка, даты подачи заявления или даты исполнения трех лет.
8⃣
 Размер пособия — один прожиточный минимум на детей в регионе.
9⃣
 От пособия в любой момент можно отказаться и использовать оставшиеся средства маткапитала по другому направлению.
🔟
 Одновременно с пособием из маткапитала можно получать единое пособие и пособие по уходу за ребенком до 1,5 лет для работающих родителей.
Источник: Минтруд
Оставьте реакцию

👍
Выплаты и Пособия
👨👩👧👦


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
😡
На Черёмушках разъярённый доставщик еды не получил чаевые и вместо них
спиздил себе новогодний дождик
 в подъезде
⚓

Хуевая Одесса
 |
Ютуб
Твиттер
 |
Прислать новость


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
🔵
🟢
💻
 У розділі «Онлайн-навчання» на вебпорталі ДПС, який містить корисну інформацію з податкової тематики, навички заповнення податкової звітності та розуміння оптимальних механізмів сплати, розміщено нові матеріали.
У підрозділах:
🖌
 «Рентна плата»
🖊
 «Податок на прибуток підприємств»
🖌
 «Податок на додану вартість»
🖋
 «Податок на доходи фізичних осіб»
🖌
 «Сплата податків та єдиного внеску, повернення платежів з бюджету»

🖋
 «Перегляд рішень територіальних органів ДПС у встановленому законодавством порядку»
🖌
 «Застосування РРО/ПРРО»
🖋
 «Інші платежі, що сплачуються до державного бюджету»
Детальніше читайте тут
👉

https://t1p.de/esvea
#ДПСінформує


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Бойцам из подразделения ВДВ «Днепр» на Херсонском направлении представители «Единой России» и фонда «Наша правда» передали универсальные лодки, что вмещают до девяти человек, оснащены мощными моторами, а в качестве бортового вооружения на них можно установить, к примеру, автоматический гранатомет.
Высокоскоростные мощные моторные лодки позволят нашим бойцам более эффективно выполнять поставленные командованием задачи.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
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Пригожин прийняв пропозицію Лукашенка про зупинення руху "Вагнера" на території Росії та подальші кроки щодо деескалації напруги.
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