Blood Collection Agency Messaging to Donors and the Public in Canada and Australia During the Early Days of COVID-19
Bibliographic record
Abstract
COVID-19 has posed unprecedented challenges to health systems around the world, including blood collection agencies (BCAs). Many countries, such as Canada and Australia, that rely on non-remunerated voluntary donors saw an initial drop in donors in the early days of the pandemic followed by a return to sufficient levels of the blood supply. BCA messaging plays a key role in communicating the needs of the blood operator, promoting and encouraging donation, educating, and connecting with the public and donors. This paper is an interpretive discourse analysis of BCA messaging in Canada and Australia from March 1-July 31, 2020 to understand how BCAs constructed donation to encourage donation during this period and what this can tell us about public trust and blood operators. Drawing on multiple sources of online content and print media, our analysis identified four dominant messages during the study period: 1) blood donation is safe; 2) blood donation is designated an essential activity; 3) blood is needed; and 4) blood donation is a response to the pandemic. In Canada and Australia, our analysis suggests that: 1) in a time of uncertainty, donors and some publics trusted the BCA to be an organization with expertise to ensure that donation is safe, essential, and able to meet patient needs; and 2) BCAs demonstrated their trustworthiness by aligning their messaging with public health and scientific experts. For BCAs, our analysis supports donor communications that are transparent and responsive to public concerns and the local context to support public trust. Beyond BCAs, health organizations and leaders cannot underestimate the importance of building and maintaining public trust as countries continue to struggle with containment of the virus and encourage vaccine uptake.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".