Building inclusive communities: the Meals on Wheels program at St. Christopher House
Bibliographic record
Abstract
This thesis is concerned with the creation of inclusive communities from the point of view of interpersonal relations in contexts of social diversity. The inclusive community is understood in this thesis as a form of social organization that brings together diverse individuals and enables them to meaningfully engage each other in interaction. The thesis illustrates the process of creation of inclusive communities through the analysis of the Meals on Wheels program at St. Christopher House in Toronto, a volunteer-based program that delivers meals to individuals who cannot look after their own nutrition. Based on this case the thesis shows that there is a significant world of social interactions beyond the practice of meal delivery that result in the form of an inclusive community. The thesis concludes by drawing lessons from the case study regarding the process of building inclusive communities as well as their role in creating social change. Copies of dissertations may be obtained by addressing your request to ProQuest, 789 E. Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106-1346. Telephone 1-800-521-3042; email: disspub@umi.com
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".