[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]
ДТП на трасі
Київ
 –
Харків
 на виїзді з Левади
😳
Хтось сьогодні знову запустив марафон аварій?
ТРУХА
⚡
Полтава
Надіслати новину


[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]
💡
Вартість електроенергії може зрости: для населення – удвічі, для бізнесу – в три рази
, — Forbes.
Вартість зруйнованого обладнання після зимових ракетних атак $8,1 млрд. Якщо тариф на електроенергію для населення зросте з 1,44-1,68 грн/кВт-год. до 2,88 грн.  ,3 грн/кВт до 4,5 грн/кВт – система фінансово збалансується.
Тому середньостатистичній людині доведеться платити на 500 грн більше, ніж платить зараз.
Надіслати новину
👈🏻
Доброго вечора, ми з Києва
👋
 |
Підписатись


[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]
🚛
Сьогодні перший день, як в Одеській області запрацювало
регулювання трафіку
 вантажного транспорту.
Станом на 18.00 отримали 105 заявок на 1202 транспортних засоби.
Комендатура вже опрацювала 78 заявок та видала 1003 перепустки.
За дотриманням нововведень на дорогах області слідкують 8 екіпажів Національної поліції.
Сподіваємося, що тепер аварій та заторів на основних артеріях Одеської області стане значно менше, також збережеться і асфальтне покриття.
📞
Підприємствам, що займаються перевезенням зернових, олійних, пально-мастильних та інших вантажів, рекомендовано звернутися до Одеської обласної державної (військової) адміністрації для консультації та подальшого отримання перепусток у комендантську годину за телефонами:
(048)718 93 87, (048) 718 95 20


[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]
Врио Главы ДНР Денис Пушилин вручил награды бойцам ЧВК "Вагнер" в ходе своей поездки в Артемовск
По его словам, они "
своими подвигами показывают, что такое русский дух, что такое сила русского оружия
".
@AG_DPR


[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]
Вуха "вагнерівців" засвітилися в Судані: допомагають одній зі сторін конфлікту
Судан не можуть поділити між собою  два зажерливих генерали. Одного з них підтримують російські спецслужби, через "вагнерівців" постачають зброю, а натомість - вивозять золото.
🫵
 Розкажу вам головне. Судан знаходиться за крок від повномасштабної війни, і тут знову не обійшлось без Московії.
👉
 Африканська країна управляється групою генералів.
 Головні з них -
Абедль Фаттах аль-Бурхан
(голова армії Судану, фактично президент) та
Мохамед Хамдан Дагло
(командир сил швидкої підтримки). Обоє розійшлися в думках щодо напрямку, в якому рухається країна, і пропонованого переходу до цивільного управління. Насправді, йдеться про гроші та впливи.
👉
 Хамдан Дагло - на короткому повідку у росіян
. Він - запеклий різник, суданська копія Прігожина. Виступає категорично проти влади цивільних, і контролює частину країни, зокрема - будівельний сектор та золоті копальні. Його хунта підтримується "вагнерівцями". Генерал торік прилітав в Москву, зустрічався з секретарем радбезу Миколою Патрушевим. В результаті кремлеві дісталась військова база на березі Червоного моря. Це, як впевнені розслідувачі, плата за підтримку "вагнерівцями".
👉
 Абедль Фаттах аль-Бурхан - практично «легітимний» керівник Судану.
 Він прийшов до влади в результаті перевороту, і зараз зміцнює свій трон. Тому наполягає, щоб війська Дагло стали частиною армії. По-перше, це дозволить підкорити конкурентне угрупування. По-друге, контролювати всі корисні копалини (в першу чергу, йдеться про золото та руду).
👉
 Конфлікт увійшов у гарячу фазу після кількох днів напруженості:
члени сил швидкої підтримки були передислоковані по всій країні, армія розцінила це як загрозу.
🫵
 Росія не перший рік паразитує на Судані, а зараз активно перешкоджає будь-якому тренду до демократизації. OCCRP провело розслідування і з'ясувало, що Прігожин підкуповує суданських чиновників, відправляє їм зброю і натомість заробляє на золоті.
👉
 Кухар Путіна працює через компанію Meroe Gold (належить "М-Інвест"), яка знаходиться під санкціями США та ЄС.
 Міністерство природних ресурсів Судану фактично передало «вагнерівцям» (читай - кремлю) золотоносні копальні, навіть не претендуючи на обіцяних 30% від зароблених на розробці коштів.
👉
 Прігожин переоформив свою компанію "М-Інвест" на родича одного з лідерів  "Єдиної Росії" Андрія Турчака.
 ЗМІ писали про його можливе призначення на посаду губернатора Санкт-Петербурга. Після цього Прігожин почав публічно атакувати та звинувачувати в бездіяльності чинного губернатора Олександра Бєглова.
👉
 Судан - одна з типових колоній кремля. Через «Вагнер» бункерний режим намагається контролювати значну територію Африки.
Конфлікт між арміями двох генералів триває. У нього можуть бути втягнутими й сусідні держави, що лише посилить кремлівське владарювання в регіоні.  Московія продовжує грабувати країну, вивозить золото і заробляє на зброї. Такий він "руський мір" в Африці.
Підписуйтеся на
"Орестократію".
 Приховане стає очевидним.


[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]
⚡
Віцепрем’єр-міністра Ірину Верещук призначено головою Координаційного штабу з питань захисту прав дитини в умовах воєнного стану

Таке рішення сьогодні прийнято на засіданні Кабміну. Коордштаб був створений у березні минулого року з метою координації дій органів виконавчої влади та місцевого самоврядування в питаннях захисту прав дитини в умовах воєнного стану.

▪
Уряд розширив перелік функцій Коордштабу. Відтепер орган:

- координує дії органів влади зі сприяння інтеграції за новим місцем проживання дітей, яких евакуйовано з небезпечних територій України;

- здійснює моніторинг дотримання прав дітей з числа внутрішньо переміщених осіб;

- координує заходи з повернення на територію України дітей, примусово переміщених на тимчасово окуповану територію або територію росії чи інших країн.

💬

«Важливо, щоб після евакуації із зон бойових дій наші діти перебували в безпеці. Для них мають бути створені належні умови проживання, навчання і психологічної реабілітації. Крім того, багато дітей були насильно депортовані агресором. У цьому питанні українські органи влади мають налагодити чіткий механізм співпраці для їх негайного повернення. Адже до вказаного процесу потрібно залучити всі інституції – від місцевого рівня до рівня міжнародних організацій. Саме на це будуть спрямовані зусилля Коордштабу»,
– наголосила Ірина Верещук.
📲
Мінреінтеграції


[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]
Дмитрий Медведев:
"Отъехавшие «туда» представители «честной элиты» предаются сладким грёзам о том, как хорошо наша страна заживёт после падения «режима» и возврата в небинарное европейское лоно. Как быстро будут свёрнуты все идеологемы ненужной патриотической войны и воцарится всеобщий праздник свободы.
Не знаю, кто из них искренне верит в это. Там разные люди с разными умственными способностями. Хотя, конечно, ни Бунина, ни Бердяева, ни Ильина, ни Шаляпина среди них нет и в помине. Так себе. Середнячки. Но одно могу сказать точно: возврата к «светлому» европейскому прошлому для них не будет".


[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]
Якщо порівняти мапу окупації  України весни 2014 з весною 2019 - то стане очевидним, що під час каденції президента Порошенка відбувалось ЗВІЛЬНЕННЯ  захоплених територій, які рф встигла загарбати, скориставшись зрадою імені Януковіча та перехідним етапом в Україні.
А якщо порівняти мапу весни 2019 з весною 2024, то ми у всій красі побачимо справжнє "проєбалі" -  бо можна обманути що завгодно, тільки не цифри на мапі.
Звідки ж взялася всенародна впевненність про "сліл Донбас", "здал Маріуполь",  "отдал Крим", а зараз би "вобщє всє здал"?
Це прекрасна ілюстрація сили кремлівської пропаганди, до якої свідомо приєдналась більша частина місцевої "еліти" та її обслуги, а народ за звичкою здуру з'їв все, що йому скормили з телевізора та ютьюба колективні мосейчук-скрипіни-іванови-шарії.
___
Для суспільства любителів астрології-тарології це не дивно - але і вижити йому з таким рівнем мислення майже неможливо;
і воно буде страждати та буквально фізично зменшуватись рівно доти, поки не навчиться робити висновки з порівняння ситуації на мапі, а не з позітівних помиїв на деградантському "єдиному".


[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]
⚡
Китай може переконати рф припинити бойові дії в Україні і повернути сторони за стіл переговорів , - Макрон на зустрічі з Сі Цзіньпіном.
Як же заїбав цей миротворець. Кордони 1991 року і тільки потім перемовини, скільки можна вже.


[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]
🧐
ЗАКОНОПРОЕКТ ПРО МНОЖИННЕ ГРОМАДЯНСТВО АНТИКОНСТИТУЦІЙНИЙ І АНТИНАРОДНИЙ!
Він протягується Зе-командою, щоб надати право іноземцям володіти українською землею та надрами!


[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]
КТО ЖИЛ В ГАЛИЦИИ?
В продолжение темы ...
В львовских гимназиях в 1913 году еще не знали украинской мовы.
Вот ничего не буду писать про политическое движение, итогом существования которого является создание целого народа.
Надоело.
Но скан живописный конечно.
👉🏻

Історія України


[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]
Швеция недавно присоединилась к НАТО, став 32-ым членом.
Уж больно боятся Россию и живут надеждой, что за деньги их шкуру защитят США в случае чего-нибудь.
Но мне кажется, простых шведов больше заботит не Россия, а мигранты, которые настолько акклиматизировались в ЕС, что напали даже на журналистов телеканала, который приехал снимать сюжет про их дружелюбность».
Как оказалось, в Швеции есть районы, куда лучше не заходить белым, ведь могут избить и 5-ая статья устава НАТО не поможет)))


[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]
👍
«Красная Армия всех сильней!»: мужчины, проживающие в городке Маллумбимби в Австралии организовали хор, исполняющий русские песни, хотя никто из них не знает русского языка.
Готовятся
🤗
Первый Патриотический
✅


[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

Потери ВСУ в технике в ходе летнего наступления, составили более 35% от переданной западной помощи (начиная с конца осени 2022 и до середины лета 2023 года).
Постоянный дефицит ощущается в грузовиках, танках, артиллерии, и боеприпасах.
Начинает ощутимо чувствоваться кадровый дефицит.
Прогнозы неутешительные.


[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]
Я дуже радий був у складі команди Президента відвідати Чехію з офіційним візитом, зокрема, Прагу, у якій часто бував раніше.
У чеському місті Злін доволі тривалий час проживала частина моєї родини. Чехія та чеський народ - це не просто партнери, а справжні друзі України.
Про це розповів у ексклюзивному інтерв’ю найбільшому суспільному радіомовнику Республіки Чехія – «Чеському радіо» (Český Rozhlas).
✅
Зазначив, що Чехія з перших днів повномасштабного російського вторгнення активно підтримує нашу державу.
✅
Для нас цей візит надзвичайно важливий. Президент Зеленський, а також уся команда прибули до Праги, щоб насамперед особисто висловити вдячність вашому Президенту, Прем’єр-міністру, уряду, спікеру та членам парламенту, а також усьому чеському народу за все, що було зроблено на користь України в ці надзвичайно складні для нашої країни дні. Україна та Чехія завжди підтримували дружні стосунки, але саме під час війни вони сягнули найвищого, історичного рівня. На нас неодмінно чекає перемога. І це буде спільна перемога.
✅
У контексті візиту української делегації до Праги напередодні саміту НАТО у Вільнюсі я зазначив, що знову переконався в непорушності позиції Чеської Республіки щодо євроатлантичних прагнень України.
✅
Україна розраховує на чіткий сигнал щодо членства в Альянсі, а також на безпекові гарантії до моменту вступу.
Сьогодні стосовно рф ми дійшли чіткого висновку: час на медіацію сплив. Альтернативою цьому процесу стала запропонована Президентом Зеленським Формула миру, яку він представив лідерам країн G19. Успішні та конструктивні консультації з представниками цих країн, а також держав Глобального Півдня в Копенгагені підтверджують зацікавленість у реалізації Української формули миру.

✅
Україна спілкується з Чехією не лише про війну, але й про майбутнє. Зокрема, про економічну співпрацю двох держав в енергетичній і  транспортній сферах, створення спільних підприємств важкої промисловості тощо.


[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]
ВСУ наконец-то получили огромное количество комплектующих для китайских и других БПЛА для полетов на дальние расстояния для ударов по инфраструктуре. Спонсором выступило британское лобби, которому выгодно, чтобы конфликт продолжался.
Начали бить по нефтебазам. На данный момент для РФ это не критично, но если таких ударов будет в сто раз больше, то это внесет некоторые нюансы во внутренний кейс, особенно на фоне предстоящих выборов в РФ.
Сейчас это больше пиар акции для Офиса Президента, который пытается сместить акцент с переноса наступления на локальные ситуативные победы. Ведь таких прилетов по Украине ежедневно происходит сотни, просто о них запретили писать и говорить.
По нашим данным, вся Европа/Ватикан, хочет заморозить конфликт, вроде как и США готово, но только британцы категорически против (Лондон не достиг своей цели - полного развала ЕС и появления нового союза с главенством Польши, плюс еще много экономических вопросов, тем более, что британские ТНК отлично зарабатывают на санкционном кейсе).


[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]
⚡
Владимир Зеленский сегодня не будет участвовать в саммите НАТО.
Об этом сообщают СМИ со ссылкой на заявление пресс-секретаря президента Сергея Никифорова
⚡
Главные итоги саммита НАТО на данный момент
▪
лидеры стран-членов приняли
долгосрочную программу военной помощи по $500 миллионов в год
 для модернизации украинской армии и полного перехода на стандарты НАТО;
▪
запуск Совета Украина-НАТО
, первое заседание состоится завтра при участии Зеленского, на нем должен быть
согласован план вступления Украины в Альянс;
▪
Коалиция из 11 стран начнет подготовку украинских пилотов на F-16 в августе
.


[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]
Проблема
махинаций с ветхими долларовыми купюрами
в обменных пунктах по всей стране, решается.
В ближайшие дни ожидаем заявление НБУ и жёсткие меры в отношении тех, кто участвовал в мошеннической схеме.
Подписаться на Харьков 1654


[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 кадрах сержант Гусенко, который отважно идет в строй к бойцам ЗСУ
Даже гуси за нас, а за тебя кто, русня?
🤣
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