“Just Shave It Off”
Bibliographic record
Abstract
Introduction Head hair comprises a critical part of the male appearance ideal, which itself is a crucial signifier of a man’s masculinity. However, difficulties in recruitment have meant that research has not yet fully explored how men construct the loss of head hair (baldness), perhaps because it is considered “feminine” to disclose body dissatisfaction experiences to a researcher or other people. Methods and Design Online forums provide an opportunity for the anonymous discussion of body dissatisfaction that may overcome this obstacle. The first 260 forums posts from the two most popular baldness forums were thematically analysed. Ethics Statement Institutional ethics approval was granted. Results and Discussion We identified three themes titled: (1) Baldness is an ugly and demasculinising condition, (2) Baldness is stigmatised by a superficial society and superficial women and (3) Resistance to baldness despair. Our findings show baldness distress, and stigma exist though so does resistance, which can be comforting to men experiencing baldness or any form of body dissatisfaction. Conclusion and Implications Online forums are a salient resource to enhance our understanding of men’s balding concerns and disclosure barriers. Independent, professional and effective baldness support that unpacks baldness masculinised and medicalised framing is recommended.
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.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".