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Record W4404822055 · doi:10.1080/18902138.2024.2430036

What men have to say about epigenetics, fertility, and masculinity

2024· article· en· W4404822055 on OpenAlexfundno aff
Matthew Kearney

Bibliographic record

VenueNORMA · 2024
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMasculinityFertilityGender studiesEpigeneticsSociologyPsychologyDemographyBiologyPopulationGenetics

Abstract

fetched live from OpenAlex

Based on interviews with an ethnically diverse, mixed-sexuality sample of 31 prospective fathers, this article considers how new health information might lead men to update roles of masculinity and fatherhood. This appears to be the first epigenetic-focused interview study of men. Subjects were queried about their reaction to newly established epigenetic findings that aspects of pre-conception male lifetstyle – not just female lifestyle – can transmit to children, and to the notion of a male fertility crisis in the sense of population-level reduction in sperm health. Their impressions of the relative male versus female contribution to the health of unborn children varied considerably, but nearly all maintained a conception of a masculine caretaker role as their primary influence on children's health. Intriguingly, they appeared potentially willing to update their diet and lifestyle behaviors in light of epigenetic findings even in ways that contravene traditional masculine associations. The masculinity literature could refer to this health-based update as emergent hybridity and caring masculinities. This article adds new information to our understanding of the social dynamics around fertility science and epigenetics.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.005
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.032
GPT teacher head0.342
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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