What's Wrong with Selling Yourself into Slavery? Paternalism and Deep Autonomy
Bibliographic record
Abstract
Such thinkers as John Stuart Mill, Gerald Dworkin, and Richard Doerflinger have appealed to the value of freedom to explain both what is wrong with slavery and what is wrong with selling oneself into slavery. Practical ethicists, including Dworkin and Doerflinger, sometimes use selling oneself into slavery in analogies intended to illustrate justifiable forms of paternalism. I argue that these thinkers have misunderstood the moral problem with slavery. Instead of being a central value in itself, I argue that freedom is a means of serving the real value of autonomy. Moreover, I argue that autonomy is ambiguous. In cases of conflict, autonomous choice, here called "shallow autonomy", can justifiably be limited to serve "deep autonomy", or self-rule. I use these notions to give a better understanding of the problem with selling oneself into slavery, and argue that the work of Dworkin has to be seriously revised, and Doerflinger's position has to be given up altogether.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".