The Farm to Fork project: Community-engaged scholarship from community partners' perspective
Bibliographic record
Abstract
Higher education institutions have traditionally largely ignored their role in identifying and addressing issues that their communities face. In an attempt to tackle this situation, models such as community-engaged scholarship (CES) have been developed and used to illustrate the active roles higher education institutions can play in sustainable social change. CES is guided by principles of mutually beneficial collaboration and reciprocity to address issues faced by the community. CES can guide the development of an in-depth understanding of social issues and can promote long-term and sustainable solutions. CES literature focuses largely on the impacts and benefits to students and faculty, but often ignores assessment of CES projects based on their impact on community partners and the community overall.This article illustrates the experiences of community partners in a Farm To Fork project and the impact of the project on community partners and the community at large. Developed at the University of Guelph in Ontario, Canada, the Farm To Fork project is helping increase the quantity and quality of food donated to emergency food providers, such as food banks and food pantries, via the use of online tools. Based on a survey questionnaire, the experiences of community partners are summarised under four categories: mutual benefit, resources, networking and collaborations, and raising awareness and addressing social issues. The results demonstrate that community partners greatly appreciate the effort and dedication of students and faculty. Through the project, community partners gained experience and access to university resources and formed networks with academics as well as other community organisations that will benefit them in the future. In addition, the Farm To Fork project helped to raise awareness about food insecurity, not only among students and faculty working on the project, but also in the Guelph-Wellington area.Keywords: community-engaged scholarship, food insecurity, community impacts, Farm To Fork, Guelph-Wellington
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.017 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".