Relevant Restaurant Interests to Partnering with Non-Profit Organizations
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
Mealshare is a newly formed non-profit organization that partners with restaurants to feed persons in need. We conducted exploratory and quantitative research on Edmonton and area restaurants to identify those restaurant interests leading to partnerships with non-profit organizations. By performing in-depth interviews with restaurant owners and managers within Edmonton, we discovered main themes such as marketing benefits of social responsibility, preferences for charities to donate to, concerns about charity work, and influences on choosing social responsibility efforts. A questionnaire was developed and distributed to restaurant owners and managers, from which we derived tentative conclusions and recommendations to enhance the Mealshare brand and identify future opportunities. Based on the findings, we find that Mealshare should focus on configuring their marketing activities to emphasize community involvement, time constraint management, and marketing benefits, as well as tailor themselves for independently owned restaurants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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