Doing Participatory Evaluation: from “Jagged World Views” to Indigenous Methodology
Bibliographic record
Abstract
Abstract The paper will present findings from a Social Science and Humanities Research (SSHRC) funded participatory evaluation conducted over the past four years in the Cree nation of Wemindji in Quebec, Canada. COOL (Challenging Our Own Limits) or “Nigawchiisuun” in Cree, was launched in 2003 as part of a broader program of governance initiatives within Wemindji. As a key component of this new governance program, COOL was to address the need for after-school care within the community for parents, as well as to engage with the recurring problem of low retention rates in school. In consultation with the Band Council of the Cree Nation of Wemindji (James Bay), the Deputy Chief at the time (Rodney Mark) – who was elected Chief in 2006 – established a COOL committee to oversee the design, organisation, implementation and running of the program. Unlike the other eight Cree communities of the James Bay, Wemindji decided to fund and run its own program based on values, customs, and traditions that have been established through consultations with elders, parents, and other interested groups within the community. This has made COOL a distinctly homegrown, autonomous, self-determined Cree program. The paper will not only report on principal themes and issues connected with the establishment and administration of COOL, but will also discuss why a participatory evaluation has been used to assess its effectiveness as a social/educational program.
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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 | 0.496 | 0.307 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.022 | 0.085 |
| Scholarly communication | 0.029 | 0.018 |
| Open science | 0.006 | 0.030 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".