Divide and Rule Better: On Subsidiarity, Legitimacy and the Epistemic Aim of Political Decision‐Making
Bibliographic record
Abstract
Abstract How should a political society be structured so as to legitimately distribute political power? One principle advanced to answer this question is the principle of subsidiarity. According to this principle, the default locus of political power is with the lowest competent political unit. This article argues that subsidiarity is a structural principle of a conception of political legitimacy informed by epistemic considerations. Broadly, the argument is that political societies organised according to the principle of subsidiarity can more effectively achieve political decisions that can justifiably appear to be correct from the point of view of those subject to them. The article presents two considerations in order to establish a pro tanto case for acting separately before presenting five additional epistemic considerations that establish a prima facie case for acting separately. The article then shows that political legitimacy and the epistemic aim of decision‐making can sometimes be served more effectively and efficiently by allowing higher‐level political units to assist lower‐level political units.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.039 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".