‘I don’t think my torso is anything to write home about’: men’s reflexive production of ‘authentic’ photos for online dating platforms
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
This paper explores men’s use of dating apps with an emergent body image focus, addressing cisgender, heterosexual men’s feelings about dating app profile pictures. Drawing from interviews with 15 cisgender, heterosexual men residing in Australia about their use of dating applications including Tinder, Hinge, and Bumble, this paper examines how cisgender, heterosexual men construct their dating app profile pictures, and the decisions they make about the content of images they use for dating profile pictures. Utilizing concepts of self-presentation, authenticity, and bodily reflexive practices, this paper argues that the men in the study are attempting to present authentic and real selves in a dating world, while being confronted by concerns regarding body image and perceptions of ideal bodies. They also demonstrate conflicting desires to appear more muscular, fit, and athletic while not presenting as vain or narcissistic. In the process of creating profiles, these men develop a sense of self drawing on understandings of masculinity and specifically notions of idealized male bodies, which simultaneously run counter to the very authentic images of the self they seek to present.
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) | 0.001 | 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) | 0.000 | 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