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Record W1716886166 · doi:10.1017/cbo9780511495564.009

Interrelation of obligations

2003· book-chapter· en· W1716886166 on OpenAlexaff
Stephen Waddams

Bibliographic record

VenueCambridge University Press eBooks · 2003
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMistakeUnjust enrichmentSubordination (linguistics)Law and economicsWrongdoingDisappointmentPolitical scienceLawEpistemologyEconomicsRestitutionPsychologyPhilosophySocial psychology

Abstract

fetched live from OpenAlex

In law, as in history, there is a complex interdependence between the particular and the general. Particular instances are analysed and understood in the light of general concepts, but the general concepts themselves have drawn their form and substance from the aggregation of particular instances. The preceding chapters have shown that many legal issues have been resolved not by subordination to a single concept but by the concurrent influence of several. This does not by any means show that concepts have been unimportant (indeed it shows the opposite) nor that they are reducible to a single inscrutable mass, but it does show that they have often interacted with each other, and that they cannot therefore be fully understood without attention to their mutual interdependence. The concepts are distinct, but in respect of many issues they have operated concurrently, influencing each other. Thus, breach of contract has been treated in Anglo-American law (differing in this respect from many other systems) as a wrong, but it cannot be entirely subordinated to the idea of wrongdoing. Even where there is no contract, the disappointment of economic expectations has sometimes been treated as a wrong, but it is not a wrong that can be understood in isolation from other concepts. Taking undue advantage of an inequality of bargaining power, or of a fundamental mistake, or retaining a benefit without rendering an anticipated benefit in exchange may cause unjust enrichments, but the law on these questions cannot be understood in terms of unjust enrichment alone.

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)0.009
metaresearch head score (Gemma)0.019
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: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0050.016
Scholarly communication0.0100.021
Open science0.0020.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0190.003

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 head0.036
GPT teacher head0.181
Teacher spread0.144 · 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
GenreOther

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

Citations0
Published2003
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicLaw, Economics, and Judicial SystemsFrench-language works237,207