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Record W2209310675

Separating Powers at the University: Applying Constitutional Law to Internal Academic Governance

2011· article· en· W2209310675 on OpenAlexaff
Bruce Pardy

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsQueen's University
Fundersnot available
KeywordsSeparation of powersBureaucracyInstitutionPolitical scienceScholarshipJurisdictionLegislatureLawCorporate governanceGovernment (linguistics)Administrative lawPublic administrationAdministration (probate law)PoliticsSociologyLaw and economicsManagement
DOInot available

Abstract

fetched live from OpenAlex

Governance of the modern university should be based upon a single principle: the separation of powers amongst its faculty, administrators, and legislative bodies. The university’s historical origins, theoretical purposes, and modern mythology are consistent with the pivotal role of separating powers in its government. Yet this principle is not generally recognized or applied, perhaps because it is so basic as to be overlooked, or because it has heretofore been expressed in terms that obscure its true nature. Authority should be divided in the following manner: University legislative bodies should have authority over operational and program matters. Administrative officers should have jurisdiction over administrative matters. Individual professors should have authority over academic matters in their courses and in their own scholarship. Such a central organizing idea would enable the parties within the institution to play complementary rather than conflicting roles. Without it, university government is liable to be arbitrary and confused, and in conflict with the institution’s conceptual foundations, resulting in problematic administration, contentious politics, and excessive bureaucracy. Separating powers within the university is important not merely because it allows the university to achieve its goals and to be consistent with its mission. Rather, it is itself the mission of the university: to provide unobstructed time and space for the free inquiry of new and controversial ideas.

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)0.027
metaresearch head score (Gemma)0.042
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 score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.042
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0110.077
Scholarly communication0.0220.020
Open science0.0020.010
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.331
Teacher spread0.295 · 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
Published2011
Admission routes1
Has abstractyes

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