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Record W2268461570

The Power to Govern Men and Things’: Patriarchal Origins of the Police Power in American Law

2005· article· en· W2268461570 on OpenAlexaff
Markus D. Dubber

Bibliographic record

VenueeYLS (Yale Law School) · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPower (physics)LawState policeLegislationState (computer science)Political scienceGovernment (linguistics)Corporate governanceSociologyLaw enforcementBusiness
DOInot available

Abstract

fetched live from OpenAlex

This article explores the genealogy of the most expansive, and yet least scrutinized, of governmental powers: the police power. The power to police, as "the power to govern men and things," is invoked in support of a vast expanse of legislation and regulation at all levels of governance, from the national government through the states and down to the smallest municipalities, including American criminal law in its entirety. At the same time it is a commonplace of American constitutional law that the police power "is, and must be from its very nature, incapable of any very exact definition or limitation." "The Power to Govern Men and Things" argues that the essential limitlessness of the police power reflects its origins in the householder's patriarchal authority over his household, including "men" (animate household resources such as wives, children, servants, slaves, and animals) and "things" (inanimate resources such as buildings, tools, and land). In the words of Blackstone's much-quoted definition, the power to police is the power of the "pater patriae" to maintain "the domestic order of the kingdom: whereby the individuals of the state, like members of a well-governed family, are bound to conform their general behaviour to the rules of propriety, good neighbourhood, and good manners: and to be decent, industrious, and inoffensive in their respective stations."

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)0.001
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: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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

Citations10
Published2005
Admission routes1
Has abstractyes

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