Social value of a Canadian urban food bank garden
Bibliographic record
Abstract
The Garden Patch—an urban agriculture program of the Saskatoon Food Bank & Learning Centre (SFBLC)—relies on corporate and individual donations in a time of growing austerity. The SFBLC does an excellent job of communicating programs to donors, but they had not previously completed a return-on-investment analysis. A social return on investment evaluation study for the 2018 growing season provided guidance on the most significant impact of the organization’s strategic objectives and provided an additional tool to communicate the program’s value to donors and the community. This work indicates the monetary value of social benefits gained from the investments made to the SFBLC for its urban agriculture program. Data sources included harvest data, volunteer logs, budget, and workshop attendance; key informant interviews with community members, volunteers, and staff; and community-based telephone and online surveys. It also included in-person surveys with community members accessing food hampers. With feedback from stakeholders, we measured the most valued program outcomes. The inputs and resources to run the Garden Patch were valued at CA$96,474 in 2018.[1] The outputs were vegetables for food hampers, gardening skills, physical and psychological health, and work and educational experiences. Outcomes were valued using financial proxies. For each outcome, the deadweight, attribution, and displacement were considered and discounted to calculate the impact value of $155,419. The final calculation is expressed as a ratio of present value divided by the value of inputs. We conservatively estimate a $1.61 of social value created for every dollar invested in the Garden Patch. We also analyze this method in the context of the current societal neoliberal paradigm, recognizing that there is much work to be done to advance food security and social justice.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".