Bibliographic record
Abstract
The way that wages are determined in a market economy produces results that strike most people as morally counterintuitive, if not positively unjust. I argue that there is an important and easily defensible principle underlying the system—it is designed to channel labour to its best employment, the way that it does any other resource. But many consider this defence too minimal, and so strive to find a thicker, more robust moral principle that can be used to defend the market, using concepts like ‘contribution’, ‘effort’, ‘laziness’, ‘skill’ or ‘talent’—all of which combine to provide a concept of ‘desert’, or ‘fairness’ in compensation. The objective of this paper is to caution against such overreach. I begin by articulating what I take to be the central principle underlying the determination of wages. I go on to discuss three different ways that both critics and defenders of the market have sought to go further than this, by introducing thicker moral concepts to the discussion, and why each of these initiatives fails. My central contention will be that markets are structurally unable to deliver ‘just’ wages, according to any everyday-moral understanding of what justice requires in cooperative interactions.
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 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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".