Perception of Aggressiveness of Communicative Information Depending on a Speaker's Gender
Bibliographic record
Abstract
Despite the great attention to the study of aggression in general, today we can see surprisingly small amount of research on the perception of aggression. Current work was inspired by the results of our previous study about prevailing perceptions of masculine and feminine aggression that showed that in general men are believed to be more aggressive, but also both for men and for women there is a tendency to consider their own aggressiveness as more high than it is in perception of the opposite gender and in general women evaluate both genders as more aggressive than men do. We were interested whether these beliefs about male and female aggressiveness will find reflection in the direct perception of communicative information. We created a computer program, consisting of the page for demographic information and the experimental part -a set of 20 aggressive and 16 non-aggressive audio phrases presented in male and female voices. It has been shown that women in general evaluate phrases as more negative, than men do, but non-aggressive phrases are perceived by women as more friendly when they are said in male voice.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".