Building Effective Community-University Partnerships: Are Universities Truly Ready?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Universities and flinders have become progressively more interested in knowledge transfer and the links between universities, democracy, and civic engagement (Ostrander, 2004). This interest has led to increase in community service learning (CSL) programs that ground academia in 'real-world' knowledge and actively contribute to the improvement of local and national social conditions (Ostrander, 2004). There has also been increase in community-based research (CBR) (e.g., Israel, Schultz, Parker, Becker, Allen, & Guzman, 2003). As early as 2003, Strand, Marullo, Cutforth, Stoecker, and Donohue predicted that combining CBR and CSL would be the next important stage of service-learning and engaged scholarship (p. 6), asserting that there is value in extending CSL models to include CBR approaches. In this article we describe a Community Psychology doctoral level course that students complete over a period of three years and that involves them in a CBR partnership with a local anti-poverty organization. In the current paper, we are concerned with the formation of the community-university research partnership rather than the findings of the CBR project itself, which will be reported elsewhere. The purpose of this paper is to contribute to the literature on university and institutional readiness when partnering with community organizations for CBR. Using our doctoral level course as example, we describe the challenges and key learnings in the early stages of developing a community-university partnership and propose methods of addressing the challenges. In particular, this paper is attempting to move beyond general discussions about institutionalization--described by Furco and Holland (2004) as the intentional incorporation of CSL throughout the institution--to assessing readiness for collaboration. We begin with a brief overview of the literature on community-university research partnerships as linked to CSL and CBR. We then describe the context of the current educational initiative in terms of the disciplinary and institutional environment, the early stages of partner identification and partnership formation, and the team research experience in community-engaged, collaborative research on poverty reduction. We end the article identifying key learnings about partnership readiness and a framework for assessing university readiness at three levels: contextual, between-group, and within-group. Background Community Service Learning Community service learning is defined by the Canadian Alliance for Community Service-Learning as an educational approach that integrates service in the community with intentional learning activities (2006, p. 1). In effective CSL initiatives, members of educational institutions and community organizations work together toward mutually beneficial outcomes. While other forms of community-based learning often passively link students to the community in a classic charity model, CSL has become a vehicle to promote genuine, collaborative, community engagement benefitting students, faculty, and community. For example, Boyer (1996) envisions CSL as a vehicle for connecting the rich resources of the university to our most pressing social, civic and ethical problems, to our children, to our schools, to our teachers and to our cities ... (p. 21). Marullo and Edwards (2000) promote a social justice approach to critical education and community-engaged scholarship, and envision transforming university operations in such a way as to allow students and faculty to function as change agents in the community. These contemporary visions of CSL seek to promote learning that addresses social problems at their root causes rather than simply ameliorating their negative impact. Similarly, Strand et al. (2003) suggest that CBR can serve as a vehicle to identify and alter the structural and institutional practices that produce social and economic inequalities. Nyden (2009) further emphasizes the transformative potential of CBR: . …
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it