Bibliographic record
Abstract
In response to the renewed importance of authenticity in contemporary culture, academic studies of authenticity are flourishing. This work contributes to the scholarship of authenticity, by exploring how authenticity is constructed in narratives of sexual identity. This work examines the narratives of 32 women who were once partnered with women and identified as queer, lesbian or bisexual and subsequently became involved with men. Although the women in this study find themselves in a position with few available scripts to make sense of the change to a partner of a different gender, they work to construct their narratives around the central theme of consistency, while grappling with notions of agency. To create authentic sexual identities, they rely on several scripts, taking into account not only what they consider authentic but also what their audience will recognize as such. The women in this study maintain that both their attraction to women and their attraction to men are authentic. Both experiences are presented as connected to some sense of internal consistency.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".