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Record W1943762756

Review Essay: The Representation of Business in English Literature

2012· article· en· W1943762756 on OpenAlexaboutno aff
Michael R. Stevens

Bibliographic record

VenueJournal of markets & morality/˜The œjournal of markets & morality · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)Argument (complex analysis)Consistency (knowledge bases)Focus (optics)HistoryCurranQuarter (Canadian coin)SociologyLiteraturePolitical scienceLawArtPoliticsComputer science
DOInot available

Abstract

fetched live from OpenAlex

An anthology is an odd species of learned text. It is neither the “flesh” of a unified argument produced by a single mind, nor the “fowl” (no pun intended!) of a wide-ranging, multifaceted journal, retooling each month or quarter. Instead, the scholarly anthology offers a set of scholarly essays, heavily footnoted, deep and narrow in focus, and often ambiguously linked. In the case of The Representation of Business in English Literature more than enough intellectual heft is offered, with contributors from some of the United Kingdom’s leading research institutions (Edinburgh, Hull, Leeds—though Oxford and Cambridge are noticeably missing). Notwithstanding, questions of consistency and breadth of focus linger over the volume from start to finish, and at times the evaluation of the literary mind seems to balance on purely mercantile terms, an unfortunate oversimplification that almost swamps the volume—almost. Nonetheless, the essays eventually rally and offer a measure of helpful insight into the world of social critique and exchange of ideas across sometimes-hostile boundaries. Michael R. Stevens, Review Essay: The Representation of Business in English Literature, Journal of Markets & Morality 13, no. 1 (Spring 2010): 205-210

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)0.012
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.272
Teacher spread0.239 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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