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Record W3161134179 · doi:10.15173/a.v1i2.2819

BAD BLOOD: THE CONDITIONS OF THE BLOOD BAN

2021· article· en· W3161134179 on OpenAlexaboutno aff
Faris Mecklai

Bibliographic record

VenueAletheia · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationMen who have sex with menOutrageContext (archaeology)Stigma (botany)CitizenshipCriminologyPolitical scienceMedicineHuman immunodeficiency virus (HIV)LawSociologyEnvironmental healthImmunologySyphilisPoliticsPsychiatryBiology

Abstract

fetched live from OpenAlex

In Canada, men who have sex with men (MSM) are not able to donate blood until three months after their last sexual encounter in order to protect the national blood supply from HIV. This policy has been regarded as highly homophobic and prejudicial as it unjustly discriminates against a specific population. The context that first called for the Blood Ban some 40 years ago no longer exists. As such, in this paper, I determine and critically analyze the conditions that have allowed the Blood Ban to not only survive, but thrive in Canada. The first condition is Canada’s history of homophobia and stigma towards HIV/AIDS. The Blood Ban was first introduced when HIV/AIDS was thought to be exclusive to the MSM community. Homophobia allowed the world to wrongfully stigmatize MSM as disease-ridden and impure and thus further perpetuated MSM discrimination and the Blood ban. The second condition is fear of possible HIV transmissions to the general public. In Canadian Blood Services (CBS) history, there have been some instances of HIV transmission occurring via blood donation. As a way to mitigate any more scandals and calm public outrage, CBS has kept the outdated Blood Ban in place. The last condition is the delegitimization of citizenship for MSM who wish to be altruistic. Altruism allows individuals to be good citizens and should be considered a right. By denying MSM to donate blood, their right to be altruistic and thus act as a good citizen is taken away and their citizenship is infringed upon. These three conditions are nuanced and act independently and in cooperation with each other to perpetuate the existence, survival, and longevity of the Blood Ban.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.965
Threshold uncertainty score0.712

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.029
Scholarly communication0.0130.005
Open science0.0010.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0060.000

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 head0.014
GPT teacher head0.231
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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