"I'm Feeding the World Tonight": The Impact of Moral Identity Standards on Mobile Loaves and Fishes Homeless Outreach Ministry
Bibliographic record
Abstract
The purpose of this study is to examine what factors motivate volunteers who work at a religiously affiliated homeless outreach organization in Texas. Specifically, the research examines the extent to which Mobile Loaves & Fishes’ (MLF) framework influences volunteers’ decisions to participate in the organization’s mobile food distribution program. Analysis of three different qualitative data sources collected in fall 2012, including organizational materials, semi-structured interviews, and ethnographic field notes, suggests that MLF’s use of framing conveys a moral identity that encourages volunteers to continue their participation in homeless outreach. This paper adds to the existing social movement literature on faith-based community development organizations (FBCDOs) by examining how religious ideology is used in tandem with elaborated framing and condensing symbols to reflect moral identity standards which induce people to volunteer.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".