Public Solicitation and The Canadian Media: Two Cases of Living Liver Donation, Two Different Stories
Bibliographic record
Abstract
BACKGROUND: . Two stories of public solicitation for living liver donors received substantial Canadian media attention in 2015: The Wagner family, with twin toddlers, each needing transplants, and Eugene Melnyk, wealthy owner of a professional hockey team. This study compared the print media coverage of these 2 stories to understand how public solicitation was portrayed and whether coverage differed depending on the individual making the plea. METHODS: We conducted a content analysis on 155 relevant Canadian newspaper articles published between January 1, 2015 and December 31, 2016. Articles were analyzed for their description of public solicitation, benefits and issues associated with public solicitation, and overall tone with respect to public solicitation. RESULTS: The foregrounding of public solicitation and associated ethical issues featured heavily in articles focused on Melnyk but were largely absent when discussing the Wagner family. The fairness of Melnyk's solicitation was the most prominent ethical issue raised. Laws and policies surrounding public solicitation also featured in the Melnyk story but not in articles focused on the Wagners. Public solicitation was portrayed more negatively in the Melnyk articles, but overall, was portrayed positively in relation to both Melnyk and the Wagner family. CONCLUSIONS: Public solicitation was generally portrayed as a positive phenomenon in Canadian print media, yet there were stark differences in how these cases were presented. The Wagner story was largely portrayed as a human-interest piece about a family in dire circumstances, whereas Melnyk's wealth, status, and influence raised questions of the fairness of his transplant.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 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".