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Record W2159635728 · doi:10.1177/1461444812465142

The intellectual and institutional properties of learning: Historical reflections on patronage, autonomy, and transaction

2012· article· en· W2159635728 on OpenAlexafffund
John Willinsky, Johanne Provençal

Bibliographic record

VenueNew Media & Society · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsUniversity of Toronto
FundersSimon Fraser University
KeywordsScholarshipAutonomyScholarly communicationPietySociologyPolitical scienceLawPublishing

Abstract

fetched live from OpenAlex

This paper attempts to cast a little historical light on current debate among scholars and publishers that appears to be over whether the academic journal is an endlessly exploitable commercial property or a public good to which all have right. It identifies key patterns in the patronage of medieval monasticism that helped to establish learning as an economically distinct form of labor, and is part of a larger historical project on the intellectual and institutional properties of learning in the West. Through the beneficence shown toward monasteries by the nobility and others, learned nuns and monks were able to operate with a degree of autonomy and trust in their scholarly work. The resulting manuscripts were directed toward the learning of others and, as such, were copied and circulated widely within the admittedly narrow confines of the monastic community. These scholarly labors became part of what attracted the continuing gifts of benefactors, who were prepared to direct a portion of their wealth to this expression of piety and discipline. This paper reflects, then, on institutional conditions that proved vital to the advancement of learning in the centuries leading up to the emergence of the university system in the Late Middle Ages. As such, it forms a point of historical reflection for the academic community today, as it reconsiders the principles by which research and scholarship should circulate within the new possibilities posed by the digital era.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.503

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.236
Teacher spread0.161 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2012
Admission routes2
Has abstractyes

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