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Record W4239286444 · doi:10.1007/978-1-349-74173-1_64

Common Law, Statute Law and Economic Efficiency

2002· book-chapter· en· W4239286444 on OpenAlexaboutno aff
Richard E. Wagner

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2002
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHistorical Economic and Legal Thought
Canadian institutionsnot available
Fundersnot available
KeywordsStatuteCommon propertyYield (engineering)Property rightsProperty (philosophy)BusinessCommon lawLawEconomicsLaw and economicsMarket economyPolitical science

Abstract

fetched live from OpenAlex

In a widely cited paper, Harold Demsetz (1967) asserted that legal rules change when economic efficiency requires them to change. He illustrated his claim with the replacement of common ownership by private ownership over fur-bearing animals around Quebec in the seventeenth and eighteenth centuries. Private property involves costs of registering and enforcing titles of ownership that do not exist with common property. Only when the gains in output that private property offers exceed those costs does it become economically efficient for private ownership to replace common ownership. Initially, the fur-bearing animals were owned in common. No person could restrict anyone else’s right to hunt. The supply of animals was plentiful relative to demand, and conflicts among hunters over animals were rare. The development of fur trading, however, added a new source of demand for fur-bearing animals. As those animals became scarcer in response to the increased demand for fur, conflicts among hunters increased because animals captured by one hunter reduced the yield that other hunters earned from their efforts. The

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.023
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.023
GPT teacher head0.251
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2002
Admission routes1
Has abstractyes

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