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Record W4242309235 · doi:10.4324/9780203892596-13

(research-based) The Commons: Disciplinary and Interdisciplinary Encounters

2010· book-chapter· en· W4242309235 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsCommonsDisciplineEngineering ethicsSociologyEnvironmental ethicsPolitical scienceEngineeringSocial sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

To attempt to understand teaching and learning within and beyond disciplinary boundaries, we must first comprehend how disciplines function and interact as social systems. In honor of the venue of this colloquium at the University of Edinburgh, and in keeping with an inclusive British tradition, I will situate my discussion in the history and philosophy of this island. The idea of ‘the commons’ provides context to explore disciplinary regions and interrelations. ‘Commons’ has three definitions in the Canadian Oxford Dictionary (1998): land set aside for public use; the common people as opposed to those in authority; the common people viewed as forming part of a political system. These definitions evoke the sense of occupied terrain that Becher (1989) suggested in Academic Tribes and Territories, but also one that is shared communally. An additional connotation, in ‘the common people versus authority’, is the challenge to traditional practices or legitimacy. The geographical origins of the commons in British history are described in the following manner:In Domesday [1086] the villages cluster thickly along the spring-line at the foot of the Downs. It was during this period that the open-field system seems to have developed: the lands of each estate were divided into two or three great open fields which were ploughed in strips by the peasantry, a system which continued right through the Middle Ages and even into the twentieth century.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.412
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
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 head0.118
GPT teacher head0.329
Teacher spread0.211 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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