Bibliographic record
Abstract
Scholars have observed workers combining multiple work roles to earn a living to cope with the vicissitudes of the labor market. In studies of creative labor markets, this trend of workers broadening of their skills is termed “occupational generalism”. Previous scholarship has focused on the structural factors that push and pull workers into generalizing and combining multiple work roles. But we lack an understanding of the subjective experience of work as a generalist. I introduce the concept of dilemma work: a form of problem-solving wherein workers who have generalized their work portfolios, attempt to rationalize their professional practices to overcome conflicts that arise from occupying multiple work roles. Drawing on in-depth interviews with professional writers who also freelance as book reviewers, I find that these generalists use three dilemma work strategies: anchoring another role to guide action in the current one; incorporating multiple roles under a higher role or purpose; and compartmentalizing roles in order to act exclusively within a single identity. I propose the general value of a typology of dilemma work for understanding workers’ experience both within artistic labor markets, and beyond.
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.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| 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".