Exploring the increasing need for plasma collection: Perspectives of voluntary nonremunerated donors on payment for plasma in Canada
Bibliographic record
Abstract
OBJECTIVES: The aim of this paper is to understand how voluntary nonremunerated plasma donors in Canada view payment for plasma and the emerging commercial sector. BACKGROUND: There is a growing global demand for plasma, to produce plasma-derived medical products. Source plasma for these products is collected through voluntary nonremunerated donation, sometimes by a national blood service, or by a commercial plasma collector, remunerating donors. METHODS/MATERIALS: This paper presents findings from qualitative semi-structured interviews with source plasma donors in three new source plasma centres in Canada. Interview data were analysed using abductive analysis, an interpretivist approach that builds on grounded theory. RESULTS: This study indicates that there are a range of perspectives on payment for plasma and the emerging commercial sector, from disinterest in payment, to opposition to payment based on the belief that it could undermine donating to help others, and risk public health and safety. One fifth of participants are open to CBS paying donors if it is necessary to increase national sufficiency of plasma. Almost two thirds of participants are opposed to commercial plasma collection in Canada, claiming that it could undermine Canada's public healthcare system, raising questions about transparency and accountability of the commercial plasma industry. CONCLUSION: Findings point to important areas for future study, on publicly collected source plasma, the emerging commercial plasma sector, and the role of the donor as a social actor in a complex political system.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.035 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| 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".