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Record W2618433515

The Decline of the Fish/Mammal Distinction?

2017· article· en· W2618433515 on OpenAlexaff
Samuel Beswick

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicProperty Rights and Legal Doctrine
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCompromiseLawSign (mathematics)SociologyHistoryPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The public/private distinction was “slain” in 1982. That year, at the Symposium of the University of Pennsylvania Law Review, Professor Duncan Kennedy set forth his six Stages of the Decline of the Public/Private Distinction, outlining the sequence by which liberal categorizations descend “from robust good health to utter decrepitude.” Professor Kennedy’s famed article concerned the history of legal thought over the course of the twentieth century. He described that history as one of “decline”—not just of the public/private distinction, but of numerous other distinctions said to “constitute the liberal way of thinking about the social world.” He pronounced on the lifecycle of these ideas and the way in which they—and the public/private distinction in particular—had become unjustifiable in legal thought. It was “[h]ard cases with large stakes” that were the first sign of trouble, precipitating compromise until distinctions all but collapsed, only to be reanimated as “continua” or pro/con “balancing” formulae6 until they became something “we can’t believe in ... any more.” In this Essay, I put to one side legal history and turn attention to the process of decline itself. For it is not only legal distinctions that are problematic. There are, indeed, many errant categorizations that fit the story of decline. My target is the so‐called fish/mammal distinction. “Fish,” it will be shown, is an indistinct category. But if it nonetheless remains acceptable for people (and biologists) to speak in terms of fish, might it be okay for people (and lawyers) to speak in terms of private law?

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.324
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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