Connecting with Communities: Researching a Community-University Partnership in Teacher Education
Bibliographic record
Abstract
While there exists a substantial body of literature on community-university partnerships, there is a notable absence of community perspective in the literature. The purpose of this study is to examine the experiences and perspectives of community members involved in a university–community partnership that developed a social justice and alternative placement program for Bachelor of Education students enrolled at a Southern Ontario University. Despite being formed with the best of intentions, authentic university-community partnerships are complex entities and are often very difficult to achieve. This study looks at the important benefits as well as significant challenges for the community partners, and how the complexity of the university-community partnership grows with the numbers of partners involved (multiple community partners in the case of my research). The experiences of the community partners are expressed through the interviews I conducted with participants. In my study, as in the case of many practitioner research studies, uncovering important knowledge about social and political issues starts from the local (community partner) perspective. This research study is meant to be a possible guide for those who wish to undertake similar work. It is my intention that the research study and findings will add insights to the theoretical and conceptual discourse on practitioner research and add to the literature reflecting community perspectives within these partnerships.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.027 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.007 |
| 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".