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Record W3035819253 · doi:10.1002/symb.495

Reframing “Dirty Work”: The Case of Homeless Shelter Workers

2020· article· en· W3035819253 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSymbolic Interaction · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsLakehead UniversityMcMaster University
Fundersnot available
KeywordsFraming (construction)Cognitive reframingSociologyEthnographyEgalitarianismEpistemologyFrame analysisSocial psychologyPsychologyLawPolitical science

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.362
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it