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
Visual, behavioral and verbal cues for gender are often used in designing virtual agents to take advantage of their stereotypical effects on the users. However, recent studies point towards a more gender-balanced view of stereotypical traits and roles in our society. This paper is intended as an effort towards a progressive and inclusive approach for gender representations in virtual agents. Our contributions are two-fold. First, in an iterative design process, we created representative male, female and androgynous agents with few differences in their visual attributes. Second, we used these agents to evaluate the stereotypical assumptions of gendered traits and roles in virtual agents. Our results showed that, indeed, gender stereotypes are not as effective as previously assumed, and androgynous agents could represent a middle-ground between gendered stereotypes. We present our findings in the hope to foster discussions in virtual agent research and the frequent stereotypical use of gender representations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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