The Metaphysics of Constitutional Precommitment
Bibliographic record
Abstract
Constitutions and bills of rights have previously been argued to be non-democratic. To justify the entrenched nature of constitutions, some theorists have argued that constitutions represent a type of rational precommitment. However, this precommitment understanding of constitutions is not without its own problems. In this work, I will argue the prominent understanding of constitutional precommitment used by its proponents seems to rely upon a definition of commitment to which their arguments do not stay true. However, when I try to amend their arguments and apply a proper example of commitment, it leads to some problems with other tenets of the constitutional debate, especially the fact of constitutional entrenchment. In an attempt to determine just what it would take to save the rational precommitment understanding of constitutions, while maintaining a proper definition of commitment, I turn to metaphysical puzzles about change, persistence, and the possibility of a mereological understanding of our constitution. I conclude that 1) current debates do not have a proper conception of commitment and are thus failing to accomplish their ends, and 2) if proponents of the rational precommitment view do not buy into my analysis, then it is going to prove quite difficult to keep their account afloat once we properly define commitment.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".