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Record W3008912886 · doi:10.7202/1067516ar

Hybrid Torts and Explanatory Tort Theory

2020· article· en· W3008912886 on OpenAlexvenueno aff
John Murphy

Bibliographic record

VenueMcGill Law Journal · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsTortLawLaw and economicsCause of actionDelictArgument (complex analysis)Equity (law)Action (physics)SociologyPolitical sciencePrivate lawComparative lawBlack letter lawPlaintiffLiability

Abstract

fetched live from OpenAlex

This article examines the problem of fit caused by “hybrid torts” for several contemporary, explanatory theories of tort law: those belonging to Ernest Weinrib, Robert Stevens, and John Goldberg and Benjamin Zipursky. The term hybrid tort is intended to capture a cause of action that is treated routinely by practitioners, judges and doctrinal jurists alike as a tort proper even though its ingredients suggest that it is only part tort and part something else (like, for example, equity). The central argument of the article is as follows: at tort law’s borders with other legal categories, there exists a number of hybrid actions that are widely acknowledged to be torts but which comprise a range of juridical components, some of which are typical within tort law and some of which are more germane to some other legal category. This set of hybrid actions suggests that—whatever theoretical neatness might dictate—tort law’s boundaries are fuzzy and porous, not clearly defined and rigid. This fuzziness in the object of theorization naturally casts doubt on the apple-pie neatness of the theories in view. In addition, the obvious response—that these juridically mixed causes of action are not proper torts (and therefore do not require explanation)—is shown to be unavailable to the theorists whose work is examined given that each of them commits to explaining the law as it presents itself. Put differently: since the law as we encounter it clearly treats these hybrid actions as torts, they cannot be dismissed in this way. Nor, it is argued—for a combination of reasons that establish their practical significance—can these hybrid torts be dismissed as irrelevant.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.022
Scholarly communication0.0040.008
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.072
GPT teacher head0.388
Teacher spread0.316 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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