"It's hard to plan your day when you have no money": Discouraged workers' occupational possibilities and the need to reconceptualize routine
Bibliographic record
Abstract
OBJECTIVE: This paper presents daily routine as a justice-related concern for unemployed people, based on an ethnographic study of discouraged workers. PARTICIPANTS: Four women and one man who wanted to work but had ceased searching for jobs, and 25 community members whose jobs served the unemployed community, participated in the study. METHODS: Ethnographic methodology--including participant observation, semi-structured and unstructured interviews, and document reviews--and the Occupational Questionnaire were used to gather data for 10 months in a rural North Carolina town. Data analysis included open and focused coding via the Atlas.ti software as well as participant review of findings and writings. RESULTS: Routines need to be seen as negotiated, resource-driven products of experience rather than automatic structures for daily living. Scholars and practitioners must acknowledge that the presence or absence of routine not only relates to resource use but also influences unemployed people's occupational possibilities. CONCLUSIONS: To address unjust expectations about unemployed people's occupational possibilities, scholars must examine the uncertain, negotiated nature of daily routine and its function as a foundation for occupational engagement. Thus, it may be helpful to view routine as both a prerequisite of occupation and a way that existing occupations are organized.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".