www.vanderbilt.edu/econ Shared Consumption: A Technological Analysis*
Bibliographic record
Abstract
*This article is a substantially revised version of the first chapter of my doctoral dissertation [Weymark (1977)]. I am grateful to Myrna Wooders for suggesting that this research is still of interest and for encouraging me to revise it for publication. The first two chapters of my thesis formed the basis of my presentation to the European Science Foundation Workshop on “Local Public Goods, Politics and Multijurisidictional Economies ” held at the Universite ́ Paris 1 (Panthéon-Sorbonne) in July 2002. I have benefitted from comments received from Jean-Marc Bonnisseau, John Conley, and an anonymous referee. I am also grateful to Karl Shell and Bob Inman for their comments on the earlier thesis version of this article and to the Canada Council for supporting my thesis research. Abstract. James Buchanan (Economica, 1966) has argued that Alfred Mar-shall’s theory of jointly-supplied goods can be extended to analyze the allo-cation of impure public goods. This article introduces a way of modelling sharing technologies for jointly-supplied goods that captures the essential features of Buchanan’s proposal. Public and private goods are special cases of shared goods obtained by appropriately specifying the sharing technol-ogy. Necessary conditions for an allocation in a shared goods economy to be Pareto optimal are identified and related to the optimality conditions for public and private goods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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; both teacher heads agree on what is shown here.
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".