How is social inequality maintained in the Global South? Critiquing the concept of dirty work
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.
Bibliographic record
Abstract
Extant research on dirty work—occupations involving physical, social, or moral taint, which affect worker identities—has been read primarily through the lens of social identity theory (SIT). There are two notable shortcomings that emerge as a consequence of dirty work being too heavily reliant upon the precepts of SIT, which we seek to remedy in this article: (1) the overemphasis on the symbolic to the detriment of the material has led to false optimism regarding the ability for subjects doing dirty work to exercise agency in constructing their own sense of selves, and (2) the failure to substantively account for the role of identity differences suggests that empirical research on the phenomenon is devoid of proper historical and cultural contextualization. Drawing on a qualitive study on low-caste toilet cleaners in Pakistan, our findings were largely incongruous with the scholarly conceptualization of dirty work that has been propagated to date. We explicate the embedded role of power and context in dirty work, which are not adequately considered using SIT alone. Repudiating the overly romanticized version of the concept, we argue that SIT’s account of dirty work ought to be complemented by status construction theory going forward.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it