Common Good Constitutionalism and the Individual—A Property Perspective
Bibliographic record
Abstract
Abstract This paper probes the position of the individual, and of their interests and rights, within a common good constitutionalism framework. To do so, it draws on long-running debates within property law and theory concerning the relative priority to be afforded to the individual and to the common good, with many of the concerns of Common Good Constitutionalism already in the mainstream of property law and theory. It compares debate about the existence, nature, and content of property’s “social function,” and its doctrinal manifestations, to Vermeule’s broad arguments about the common good dimensions of constitutionalism. Specifically, it analyzes the effectiveness and purpose of an “internal limitation” strategy, and the risk of excessive individual subordination to collective interests. Finally, it assesses how central a role coercive legal measures should play in encouraging virtuous conduct within a common good constitutionalism framework.
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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 | 0.002 | 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 | 0.004 |
| 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".