Peut-on se distancier du regard masculin? Voyons ce qu’en disent les femmes « mûres » sur Instagram
Bibliographic record
Abstract
Don't you have the impression that women over forty are condemned to fade into the background or disappear from the public space? At last, that's the message fashion magazines seem to be sending us. Yet, one only has to browse through Instagram to realize that fashionistas who left the world of adolescence long ago are proudly displaying themselves in swimsuits or in the latest trendy clothes, sometimes colorful and sometimes extravagant. How do these women - who are called mature women or women of a certain age - put themselves forward? Do they manage to get out of the grip of the male gaze or do they perpetuate the traditional codes of advertisement and fashion? This question is one that seems to lend itself well to the Instagram platform since, by being the transmitters of information, these female influencers allow us to evaluate their submission or resistance to the dominant discourse. This exploratory study, focusing on the Instagram accounts of four female influencers aged between 42 and 64, offers some answers and reflections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".