Where are all the gay fathers?: Reflections on recruiting gay fathers as participants in leisure research
Bibliographic record
Abstract
There is a dearth of understanding of gay fathers’ perspectives on leisure studies topics. If researchers are to conduct research that better reflects all fathers, it is important to gain insights into recruiting gay fathers, and to ensure that gay fathers know that their perspectives are needed and desired. Thus, in this research note, we highlight two important reflections on the difficulties we encountered when attempting to recruit gay fathers as research participants: (1) Heteronormativity exists in leisure studies and it is problematic for the recruitment of gay fathers; and (2) understaffed organisations are at times unable to help recruit gay fathers for research. Researchers who work with gay fathers may draw on our reflections to overcome similar difficulties that they may face. It is our hope that our reflections may contribute towards achieving the important social justice goal of including gay fathers in leisure studies.
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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 | 0.083 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.045 | 0.028 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.012 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".