Managing spoiled identities: dirty workers' struggles for a favourable sense of self
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore how a group of dirty workers, that is, exotic dancers employed in a gentlemen's club, engage in identity construction amidst various macro, meso and micro considerations. Design/methodology/approach This study adopts a social constructivist approach in exploring the stories of a group of 21 dancers employed at a chain of exotic dancing clubs in the UK, For Your Eyes Only. Findings Identity construction is a complex process whereby dancers struggle to secure a positive sense of self among the various resources they encounter. The findings focus upon the processes of distancing through projecting disgust upon clients, other dancers and other clubs. Dancers do this to minimize the stigma associated with their own identities and position themselves in a more favourable light to others. In doing this, dancers construct a variety of identity roles for themselves and “others.” This process of distancing also results in the construction of a hierarchy of stigmatization whereby dancers categorize motivations for dancing, type of dancing and type of clubs to rationalize the work they perform and manage their spoiled identities. Practical implications The stories of these dancers illustrate the messy nature of identity construction for dirty workers. In turn, it also illuminates how a better understanding of the complexity of identity construction for exotic dancers can offer insights transferable to other dirty work occupations and organizations in general. Originality/value The paper provides an indepth look at an occupational site that is relatively unexplored in organization studies and thus makes a unique empirical contribution. It also offers a more comprehensive theoretical lens for understanding identity construction and dirty workers.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.037 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".