Reframing “Dirty Work”: The Case of Homeless Shelter Workers
Bibliographic record
Abstract
Drawing on ethnographic research in a homeless shelter, this article examines how caseworkers navigate an occupation that is often physically and morally trying, and at times, objectionable. Given this context, we examine the ways in which caseworkers identify and define “dirty work,” often seen as a source of occupational degradation, according to two main typifications: the physical and the moral. Building on Erving Goffman's frame analysis, we examine the definitional and interactional strategies actors use to transform unpleasant first‐order realities to more valued, meaningful, or workable second order realities, by keying particular frames of meaning. These involve framing dirty work through (1) a professional lens, (2) humanism and egalitarianism, (3) a negotiated interpretation of institutional rules, and (4) the use of humor. We conclude by reflecting on the constructed nature of dirty work, and the importance of framing strategies in the sociology of occupations, suggesting that a more generic application of these ideas may be useful across a number of other social contexts.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.039 | 0.033 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".