The Frequency of Blood Donation in Canada: An Exploration of Individual and Contextual Determinants
Bibliographic record
Abstract
Blood products are used for transfusion in many routine procedures as well as emergency medical care. The balance between the supply and demand of blood products in Canada is being threatened by an increasing aging population, a growing immigrant population, and advances in medical technology which places additional strain on the blood supply. The objective of this research is to investigate the effects of demographic determinants and clinic accessibility on the frequency of blood donation in Canada excluding the province of Québec, providing a national assessment of blood donor correlates at the individual level. Exploration of these demographic factors in addition to clinic accessibility may help to explain why a limited number of repeat donors are currently contributing, with many donors giving blood only once a year. Repeat donors are vital to maintain a safe and secure blood supply, therefore it is important to retain existing donors in addition to recruiting new volunteers. In this study, individual donor and clinic information is obtained from the Canadian Blood Services 2008 national dataset, with contextual data from the 2006 Canadian Census. Discrete choice models are used to assess the effects of these variables on the frequency of blood donation across the country, highlighting the importance of clinic accessibility. The analysis is prepared for major Census Metropolitan Areas in Canada. Results may contribute to service optimization and targeted advertising, ultimately aiming to encourage the eligible population to donate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".