Saudi Gender Emotional Expressions in Using Instagram
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are plentiful studies exploring gender emotional differences. Gender and emotion stereotypes make people believe that there are certain emotions associated with each gender and this is supported by many studies. The purpose of this research is to analyze the emotional expressions of Saudi men and women in Instagram, a social networking service. This paper aims to explore the Saudi differences of emotional expressions. Also, if gender emotion stereotypes apply on these expressions or not. Data is collected through corpus analysis of Arabic comments for a certain post on Instagram. The results of this study demonstrate that there are differences in Saudis' expressions of emotions in which each gender uses different expressions. Additionally, gender stereotypes of emotions are applied to their emotional expressions that is men express negative emotions more while women express positive emotions. Another result is that women are found to be more emotional than men. Overall, the findings contribute to increase understanding of online emotional expressions of both Saudi genders.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it