Deploying an ethics needs assessment to inform a navigational tool for research compliance pathways at a provincial Canadian health authority
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Practitioners aim to improve healthcare systems and clinical care through a variety of activities as part of a learning healthcare system. Yet the distinction between projects requiring Research Ethics Board (REB) approval or not is becoming increasingly blurred, making it difficult for researchers and others to classify projects and then navigate the required compliance pathway appropriately. To address this challenge, the Provincial Health Services Authority (PHSA) of British Columbia (BC) created a decision tool called the "PHSA Project Sorter Tool" to serve its diverse community while also meeting the unique needs of the BC regulatory and policy environment. The goal of the tool was to standardize and clarify organizational project review and ensure project leads were referred to the appropriate review body or service provider within the PHSA in the most efficient manner possible. In this paper, we describe the ethics needs assessment that was conducted to inform the tool and the results of our ongoing evaluation of the tool since it was launched in January, 2020. Our project shows that this simple tool can reduce burdens on staff and provide clarity to users by standardizing processes and terms and directing users to appropriate internal resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.218 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.014 |
| 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 it