“I'm not your reality show:” Perspectives of bereaved mothers' engagement with the news media to advance drug policy reform
Bibliographic record
Abstract
North America's overdose crisis is one of the most urgent public health issues of our time and parents bereaved from substance use are a prominent voice within the news media. To date, however, the experiences of bereaved mothers who have shared their stories with the media has not been well-documented, leaving a significant gap in our understanding of their political advocacy efforts. In 2017, we conducted qualitative interviews with 43 mothers across Canada who participated in drug policy advocacy following the substance-related death of their child. We used a narrative interview approach and thematic analysis to distill key themes in recounting bereaved mothers’ stories of engaging with reporters, their perspectives on media representation and the personal impacts of sharing their stories with news media. Participants viewed the news media as powerful allies in educating the public, changing attitudes, and ultimately influencing policy in support of people who use substances. However, there was a personal cost that accompanied this media advocacy which included the potential for sensationalism, news media complacency, insensitive comments by journalists, and having one's story misrepresented. Our study highlights the complex relationship between mothers bereaved by substance use and the news media who hold tremendous power in framing their stories. By examining bereaved mothers as social movement actors and reflecting on the structural context in which news stories are delivered, we outline strategies to ensure parents bereaved by substance use can safely share their stories with media and continue their work in countering stigma and misinformation.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".