Finding food suppliers & producers with aligned environmental and social justice values
Bibliographic record
Abstract
Global warming is likely to reach 1.5℃ warmer than pre-industrial levels between 2030 and 2052, with anthropogenic emissions contributing up to 1.0℃ (IPCC, 2019). The effects of climate change stemming from unsustainable energy use, land-use change, and production and consumption patterns are likely to cause global long-term challenges, particularly in agricultural production and food systems (IPCC, 2019). Research shows that 34% of global greenhouse gas (GHG) emissions are from food systems, and immediate action is required to mitigate and adapt to the effects of accelerated global warming (Crippa et al., 2021). Large institutions such as the University of British Columbia (UBC) have significant purchasing power in their food procurement processes, offering the opportunity to exemplify how institutions can play a vital role in mitigating GHG emissions, ultimately fostering more ethical and environmentally conscious food systems. This project is in alignment with UBC’s strategic commitment to creating a Climate-Friendly Food System (CFFS), which aims to reduce the GHG emissions of the campus’ food system by 50% by 2030 (UBC, 2021). One of the short-term actions to be executed by UBC in 2024 is the development and implementation of campus-wide sustainable food procurement guidelines to align with the goals of both CFFS and other international climate change agreements (IPCC, 2019 UBC, 2021). Overall, this research aims to contribute to the development of said guidelines. Guided by Community-Based Action Research (CBAR) principles, the methodology employed in this research included community engagement, shared decision-making, ethical considerations, cultural sensitivity, and transparent communication (Gullion & Tilton, 2020). Methodological tools included literature reviews to identify the sustainability practices of current and potential food suppliers at UBC, a review of UBC’s policies related to climate action and food systems, stakeholder meetings with UBC Student Housing and Community Services (SHCS), UBC Alma Mater Society (AMS), and UBC Social Ecological Environmental Development (SEEDS) representatives. Primary data was collected through surveys and interviews with current and potential suppliers, and an evaluation of this primary data through a sustainability matrix scoring system. The objectives of the research were to evaluate the sustainability and social practices of potential and current food suppliers of UBC SHCS and UBC AMS, identify potential food suppliers whose values align with UBC’s existing sustainability policies and commitments to create a more sustainable campus food system, and to propose a methodology for continuous improvement in the food procurement process for both UBC and other large educational institutions. Through our sustainability evaluation matrix, we were able to identify three potential suppliers in the categories of meat, grocery, and eggs that demonstrated exemplary performance in sustainable and just business practices. These food suppliers align with the university’s multiple strategic commitments to environmental sustainability and social justice and may serve as new food suppliers for UBC SHCS and UBC AMS. The project’s main deliverable was to utilize the analyzed primary and secondary data to conduct a “Strengths, Weaknesses, Opportunities, and Threats” (SWOT) analysis for UBC's current and potential food vendors. This analysis may serve as a methodology for improving the food procurement processes at UBC and beyond. Through this analysis, it was revealed that a key strength of many suppliers was their efforts reduce their carbon footprint throughout the supply chain, as well as supporting local economies through local food sourcing. Conversely, a main challenge for many suppliers was their limited ability to scale production or supply to meet the demands of large institutions like UBC. Overall, our short-term recommendations for UBC SHCS and UBC AMS include maintaining and exploring new relationships with the identified ideal suppliers. In the long term, we recommend continued research into the role of educational institutions in supporting Climate Food System Action (CFSA), for example by supporting local food systems and economies, as well as collaborating with cross-sector organizations. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.007 |
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".