Building Capacity for Community Engagement in the Research Ethics Process.
Bibliographic record
Abstract
Background: Institutional research ethics processes are often far removed from both research participants and community-based organizations. We present our ongoing efforts to develop a community-based research ethics process for newcomer groups in Calgary. Approach: A needs assessment carried out in 2020 identified the following issues: • Research conducted about newcomers in Alberta is generally not accessible to agencies, community members or research participants; • Immigrant serving agencies and community organizations rarely feel they are engaged as full partners in research projects led by academic researchers; • Immigrant serving agencies and academic researchers operate in different contexts, leading to divergent ideas about what constitutes ‘ethical practice’ in research. (Bragg, 2020) Following a review of the literature on community-based ethics processes and consultation with founders of two community-based research ethics boards (Jane Finch Community Research Partnership, 2021; Neufeld et al, 2019), we have taken the following initial steps: • Launched the Newcomer Research Library profiling plain-language summaries of Alberta-based research; • CCIS has successfully implemented a research screen and process for more equitable academic processes; • Recruited a representative from the CCCIS to sit on the University of Calgary’s social science research ethics board. This board member reports back to the community regularly on the university-based ethics processes. Observations / Conclusion Working across institutional boundaries has been fruitful and empowering. We anticipate next steps will include convening community conversations with past research and engaging with partners and key stakeholders with the aim of developing research principles and later establishing a community-based research ethics process. References: Bragg, B. (2020). A strategy for equity in research with newcomers. Summary report produced for the CCIS / MITACS Partnership. Neufeld et al. (2019). Research 101: A process for developing local guidelines for ethical research in heavily researched communities. Harm Reduction Journal 16:41. https://doi.org/10.1186/s12954-019- 0315-5 Jane Finch Community Research Partnership (2021). Principles for Conducting Research in the Jane Finch Community. https://janefinchresearch.ca/research-principles
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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 | 0.317 | 0.268 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.023 | 0.072 |
| Scholarly communication | 0.029 | 0.028 |
| Open science | 0.006 | 0.079 |
| Research integrity | 0.010 | 0.024 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".