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Understanding Canadian student motivations and beliefs about giving blood

2005· article· en· W2053141064 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTransfusion · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDonationConceptualizationBivariate analysisBlood donorPsychologyVariance (accounting)Altruism (biology)Social psychologyPsychological interventionLogistic regressionMultivariate analysis of varianceClinical psychologyMedicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: A better understanding of Canadian blood donor beliefs and motivations is needed to develop targeted interventions. Recruiters must know how motivation variables and correlation patterns differ with donor experience and sex. STUDY DESIGN AND METHODS: Data addressing reasons for donating, statements about the blood supply, beliefs about donation consequences, and reasons for avoiding donation were collected from 450 undergraduates. Principal components analysis was used to investigate the underlying factorial structure of each domain. Men-women and donor-nondonor differences were explored with multivariate analysis of variance techniques. RESULTS: A bivariate model better represented donor beliefs than did a bipolar conceptualization. Negative beliefs distinguished donors and nondonors more so than did positive factors. Altruism dominated reasons for donating, whereas logistic factors accounted for the most variance in donation avoidance. Women were more concerned about adverse physical consequences, and nondonors expressed higher levels of groundless donation-related fears. CONCLUSION: Recruiters should consider the sex and donation experience of targets when they develop recruitment and retention strategies. Education programs aimed at overcoming fears and heightening awareness of need are recommended, as are operational improvements aimed at reducing barriers posed by time and inconvenience.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.250
Teacher spread0.206 · 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