Bibliographic record
Abstract
“What’s faith got to do with it?” In this paper we explore the multilayered role of faith in two food banks in Toronto. We are drawing on a larger study of five partnerships between faithbased organizations and others for the common good, a study that unpacks the interesting dynamics of collaborations involving at least one faith partner. In the selection we have made for our present paper, the reader can expect to find a description and analysis of those dynamics as they pertain to individuals, groups, religious and secular organizations, new immigrants and long time residents, a rich variety of faith groups—all around the issues of having enough to eat, human dignity and the formation of community. When we use the word “faith” we are aware of the multiplicity of meanings carried by the term. There is a basic distinction, famously formulated by Wilfred Cantwell Smith, between the faith that animates and is held by an individual and ‘a faith’ in the sense of a world religion, which has a history, traditions, sacred texts, liturgy, normative practices, teachings, creeds, buildings, authorized leaders— in short all the characteristics of a religion established over many centuries. Of course, there is a symbiotic relationship between the personal and the institutional. Each enlarges and enriches the other; neither can exist without the other. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series,TRSM, Ted Rogers School of Management Citation:
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".