Using Indigenous Methodologies to Evaluate School Community Councils in Saskatchewan
Bibliographic record
Abstract
Abstract In 2018, the author undertook a learning-oriented evaluation (Dahler-Larsen, 2009) of School Community Councils (SCCs) in Saskatchewan. The evaluation sought to determine the current state of SCCs in relation to achieving their mandate and engaged approximately 120 participants. To achieve a critical analysis of SCCs in Saskatchewan, the author also conducted a culturally responsive evaluation (Hopson, 2009; Mertens & Zimmerman, 2015) by interviewing four non-SCC parents (Indigenous, immigrant newcomers, and visible minority). As an Indigenous researcher, it was important to the author that this evaluation was situated within a context that respected and reflected who the author is as Métis and that it was carried out in a way that honored Indigenous approaches (Battiste, 2013; Cardinal & Hildebrandt, 2000; Kovach, 2009; Tuhiwai Smith, 1999) with a view to putting the principles of respect, relationality, and reciprocity into action. In this chapter, the author describes the tension the author experienced as an Indigenous researcher when confronted with pursuing evaluation through Western research methodologies, including ethnography. The author describes how the author centered Indigenous methodologies (Kovach, 2009) within an evaluation tradition (Ryan & Cousins, 2009) by formulating the study in Indigenous theory, situating the author in the study, and bringing Indigenous approaches as the primary methods in a culturally responsive evaluation (Bowman et al., 2015; Hopson, 2009; Kovach, 2009; LaFrance et al., 2012). Decolonizing research is a process, and the author offers this chapter to encourage Indigenous researchers to embrace this tension, build upon lessons learned, and continually refine the understanding and practice of utilizing Indigenous methodologies in evaluation.
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How this classification was reachedexpand
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".