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Record W4393952350 · doi:10.32920/25438513

It’s in Me to Give: Canadian Gay, Bisexual, and Queer Men’s Willingness to Donate Blood If Eligible Despite Feelings of Policy Discrimination

2024· preprint· en· W4393952350 on OpenAlexaffabout
Daniel Grace, Mark Gaspar, Ben Klassen, David Lessard, David J. Brennan, Nathan J. Lachowsky, Barry D. Adam, Joseph Cox, Gilles Lambert, Praney Anand, Jody Jollimore, David Moore, Trevor Hart

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsAIDS VancouverUniversity of British ColumbiaInstitut National de Santé Publique du QuébecUniversity of WindsorUniversity of VictoriaMcGill UniversityCommunity Based Research CentreToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsQueerFeelingPsychologySocial psychologyHomosexualityGender studiesSociologyPsychoanalysis

Abstract

fetched live from OpenAlex

<p>Blood donation policies governing men who have sex with men have shifted significantly over time in Canada—from an initial lifetime ban in the wake of the AIDS crisis to successive phases of time-based deferment requiring periods of sexual abstinence (5 years to 1 year to 3 months). We interviewed 39 HIV-negative gay, bisexual, queer, and other sexual minority men (GBM) in Vancouver, Toronto, and Montreal to understand their willingness to donate blood if eligible. Transcripts were coded following inductive thematic analysis. We found interrelated and competing expressions of <em>biological</em> and <em>sexual citizenship</em>. Most participants said they were “safe”/“low risk” and “willing” donors and would gain satisfaction and civic pride from donation. Conversely, a smaller group neither prioritized the collectivizing biological citizenship goals associated with expanding blood donation access nor saw this as part of sexual citizenship priorities. Considerable repair work is required by Canada’s blood operators to build trust with diverse GBM communities.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.316
Teacher spread0.280 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2024
Admission routes2
Has abstractyes

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