The Cost of a Free Lunch: Transforming Food Aid Fundraising Towards Leveraging Systems Change
Bibliographic record
Abstract
This project explores opportunities to support systemic change through the unique lens of fundraising, focusing specifically on donor relations practices, power imbalances, and the impact language has on the charitable food aid system. The primary purpose of this research study is to provide a set of recommendations for charitable food aid organizations to transform donor relations practices with the overall goal of building relationships that are geared towards leveraging long-term change within the food security system. Food insecurity is a complex problem that continues to persist despite decades of food aid, with the demand continuing to rapidly increase due to the ongoing impact of the COVID-19 pandemic and record high inflation rates. Addressing the immediate need of hunger relief are charitable food programs that operate on a continuous need for funding, which results in a significant ongoing organizational investment in fundraising activities. Funding is crucial to sustain food program operations and continue to address the immediate need, however the demand for funding creates a cyclical and transactional relationship between charities and donors. This project explores the unintended consequences of the cycle of fundraising within the context of charitable food aid, and identifies opportunities within fundraising to promote donor relationships that are focused on affecting long-term systemic change. This project completed the following research deliverables: i) literature review, ii) current state system map analysis, iii) web-based survey with food aid fundraising professionals working at food aid charities based in the Greater Toronto Area, iiii) development of actionable recommendations for fundraisers working in food aid to implement in their practice. The literature review highlighted multiple topics relevant to this research, which informed the selection of systems theory as the conceptual framework for this project. This research draws from both Gap Analysis and Promising Practices methodologies, as well as some principles from Community Engaged Research. The current state system map analysis was conducted utilizing systems mapping within systems theory to understand the role of fundraising within the status quo of the system, and identify where change is feasible within the cycle of fundraising. The web-based survey was thematically analyzed and deductively coded to capture fundraiser perspectives on this topic and support the development of recommendations as the final project deliverable, based on the findings from both the system map and the survey. This research demonstrates that the opportunity for transformation within food aid fundraising exists, and provides recommendations for fundraising professionals for real world application.
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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".