'Crafting' Curricula and Pedagogies Examining Efforts to De-center Sheridan College's Furniture Studio Through Indigenous Community Engagement
Bibliographic record
Abstract
This Major Research Project (MRP) investigates the efforts to de-center the curricula and pedagogies of Sheridan College’s Furniture Studio by meaningfully engaging with Indigenous communities. The research focuses on two community engagement projects where third-year Furniture students engaged with members of Thunder Bay’s Indigenous community to co-create furniture for the Indigenous Knowledge Centres of two branches of the Thunder Bay Public Library. Using qualitative ethnographic research methods, including questionnaires, a semi-structured interview, and focus groups, this study examines how these projects impacted both Indigenous participants and student participants involved in the two projects. The outcome of the study finds significant benefits which include an increased awareness and appreciation of Indigenous culture and knowledge among students, and a strong sense of ownership and pride among Indigenous participants. Challenges identified include the need for preparatory intercultural competency training for students, greater management of power imbalances, extended project timelines to facilitate deeper relationship building, and the need for further benefits to the Indigenous community. This research aims to contribute to the discourse on decolonizing craft and design education and promote an inclusive design framework by showcasing practical applications of these principles. It underscores the transformative potential of integrating Indigenous knowledge into educational practices and offers recommendations for future projects to further these efforts towards equity and inclusion.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".