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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 As a way to mitigate any more scandals and calm public outrage, CBS has kept the outdated Blood Ban in place.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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.904
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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