Community Engagement in the Humanities, Arts, and Social Sciences: Academic Dispositions, Institutional Dilemmas
Bibliographic record
Abstract
In April 2014, McMaster University and Carleton University collaborated with Kugluktuk, an Inuit community in Nunavut to survey community views on resource development and produce a larger community report. This was part of a Community Readiness Initiative (CRI) piloted by the Canadian Northern Development Agency (CanNor) to assess the socio-economic needs of communities across the North prior to mine development. Kugluktuk is the first of seven communities across Nunavut, the Northwest Territories, and the Yukon to produce their final report. Universities have started to play an important role in developing a ‘third mission’ whereby researchers are encouraged to collaborate with non-academic organizations. This collaborative approach can include contract research and consulting, as well as informal activities like providing ad hoc advice and networking with practitioners. Working as an academic in this environment can create tensions, but it can also create opportunities to foster and ensure meaningful input and consultation from a variety of stakeholders. This paper focuses in depth on the collaborative nature of the CRI process that began in April 2014 and ended in August 2015 with an emphasis on the community-based participatory research approach that we took. With insights that apply equally well outside of the Kugluktuk context, the approach that we took also provides a useful model for engaging with issues on mining and resource development opportunities.
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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 | 0.099 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.101 | 0.116 |
| Scholarly communication | 0.046 | 0.023 |
| Open science | 0.005 | 0.061 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".