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Record W3167947420 · doi:10.1177/10608265211018817

A Men’s Survey: Exploring Well-Being, Healthy Relationships and Violence Prevention

2021· article· en· W3167947420 on OpenAlexafffundabout
Liza Lorenzetti, Vic Lantion, David Este, Percy Murwisi, Jeff Halvorsen, Tatiana Oshchepkova, Hemlata Sadhwani, Fanny Oliphant, Adrian Wolfleg, Michael A. Hoyt

Bibliographic record

VenueThe Journal of Men s Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsAlberta HealthNetwork for Business SustainabilityUniversity of Calgary
FundersCalgary Foundation
KeywordsIndigenousPsychologyPopulationDomestic violenceSuicide preventionGerontologyGender studiesPoison controlSociologyMedicineDemographyEnvironmental health

Abstract

fetched live from OpenAlex

The participation of men is critical to preventing domestic violence, however, there is still little understanding of the capacities and supports that men need for well-being and healthy relationships. A men’s survey was designed to explore and identify the capacities and resources required by a diverse population of Canadian men. Data was collected on-line and through trained community-based research assistants. Over 2,000 men from 20 ethno-cultural groups responded, and multiple challenges and enablers were identified. Responses from Indigenous and African Canadian men highlight the need for an intersectional lens in understanding men’s well-being and violence prevention.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.708

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.194
GPT teacher head0.399
Teacher spread0.205 · 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 designObservational
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

Citations5
Published2021
Admission routes3
Has abstractyes

Explore more

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