Bidirectional consultative process as a novel methodology to develop a pan-Canadian cancer quality initiative.
Bibliographic record
Abstract
80 Background: To foster pan-Canadian quality improvement strategies in cancer diagnosis and treatment, a new publically funded opportunity was launched though a Request for Proposals (RFP). Methods to develop RFPs in the public health care sector are variable. To generate enthusiasm and ensure appropriateness and relevance of the RFP, a novel methodology was developed to refine and validate the focus of the RFP. Methods: An extensive multi-pronged bi-directional consultative process helped identify and engage with clinical experts, senior administrators, and other relevant stakeholders. In-person discussions with relevant stakeholders, an electronic stakeholder engagement survey, and two interactive electronic information sessions (Webinars) were included. The intent of the eBlast was to seek survey responses and also to build awareness of the upcoming opportunity. An eBlast engaged stakeholders and stakeholder networks for the electronic component of the bi-directional process. Secondary distribution encouraged wide-spread dissemination. The survey and recorded Webinar were publically posted online. Results: Approximately 30 in-person consultations occurred and the electronic survey and Webinar details were sent to approximate 1,000 individuals and external networks. 80 responses were received along with 76 Webinar attendees. Feedback was received from a representative cross-section of the Canadian quality community as measured by geographical distribution and discipline. There was general pan-Canadian agreement that the quality topic chosen was relevant and appropriate. Through this methodology refinements were made to finalize the organization and content of the RFP. Conclusions: When developing a national call for a publicly-funded quality improvement opportunity, it is imperative to ensure the topic considered is relevant, appropriate, and there is interest from stakeholders to apply. A bi-directional consultative process is a novel and economical method to ensure wide reaching engagement from relevant pan-Canadian stakeholders. This methodology can also be leveraged to refine and validate the final quality topic considered.
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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 | 0.237 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.006 | 0.024 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".