‘I just want to be able to make a choice’: Results from citizen deliberations about mammography screening in Ontario, Canada
Bibliographic record
Abstract
Despite Canada's long history with mammography screening, little is known about citizens' perspectives about mammography and how best to support women to make informed choices about screening. To address this gap, a series of four citizen deliberation events were held in 2015-16 in Ontario, a Canadian province with an organized population-based breast screening program in place since 1990. Forty-nine individuals participated in four citizen panels, each comprising an information session highlighting the evidence about mammography, and large- and small-group deliberations about approaches to support informed decision making for screening. Following their engagement with the research evidence about mammography, participants expressed concern about their lack of full awareness of the risks and benefits and a strong desire for choice when it comes to screening. To support informed choice, mammography programs need to reflect the values of information sharing, trust and transparency, financial accountability, and allow for personal interactions and shared decision-making. Citizens are looking for balanced information about the risks and benefits of screening presented in an easy to understand, comprehensive, and transparent manner. Primary health care providers and organized screening programs are important sources of information about mammography and must be vigilant in their efforts to support informed decision-making in this area by ensuring that the information materials they are using are balanced and reflect current evidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".