Researching Men and Masculinities as a Woman: A Feminist Geography Reflection
Bibliographic record
Abstract
Feminist research on men and masculinities contributes valuable understandings toward gender negotiations and relations in leisure. However, feminist women researchers often face safety concerns while pursuing projects with men participants and within masculine-dominated spaces. The purpose of this article is to provide a feminist geography perspective on a woman researcher’s experiences researching men and masculinities in the strength-based area of a fitness center. The reflections were generated from six months of participant observations in a Canadian university fitness center and were analyzed using reflexive thematic analysis. The findings consider the impact of researchers being the object of sexualization and questioning and its implications on their experience of body, identity, and power in the field and with participants. It contributes to knowledge surrounding relational politics in fieldwork and ethnographic-based research in masculine-dominated spaces.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.055 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| 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".