Negotiating With Gender Stereotypes on Social Networking Sites
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
Research indicates that stereotypical representations of girls as sexualized objects seeking male attention are commonly found in social networking sites. This article presents the results of a qualitative study that examined how young women “read” these stereotypes. Our participants understood Social networking sites (SNS) as a commoditized environment in which stereotypical kinds of self-exposure by girls are markers of social success and popularity. As such, these images are “socially facilitative” for young women. However, the gendered risks of judgment according to familiar stereotypical norms are heightened by the intense surveillance enabled by SNS. While our participants indicated that a mediatized celebrity culture inculcates girls with messages that they must be attractive, have a boyfriend, and be part of the party scene, girls are much more likely than boys to be harshly judged for emphasizing these elements in their online profiles. Girls are also open to harsh criticism for their degree of publicness. The risk of being called a “slut” for having an open profile, too many friends, or posting too much information suggests that continuing discriminatory standards around public participation may effectively police girls’ capacity to fully participate online and complicate their ability to participate in defiant gender performances.
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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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