Bibliographic record
Abstract
Care exploitation pervades our lives. Consider the public school teachers who care about helping children achieve their goals by providing them with a proper education and are expected to do so by parents, administrators, or legislators—even with abysmal pay and little appreciation. Perhaps the most common case of care exploitation is the expectation of a mother to make great (and disproportionate) sacrifices in her life for the well-being of her child, which mothers often meet because they bear a caring orientation toward their child. Despite their willingly assenting, there is something morally problematic about their treatment. I argue that an injustice has been perpetrated against them, drawing on interpersonal accounts of exploitation to highlight that the unique wrong of care exploitation is the failure to respect one’s dignity by taking advantage of their vulnerability of caring about. Following this, I articulate the necessary and jointly sufficient conditions of care exploitation and their relationships to one another.
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 | 0.004 | 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 | 0.012 | 0.025 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".