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Record W2498981201 · doi:10.1515/bap-2015-0026

Merely TINCering around: the shifting private authority of technology, information and news corporations

2016· article· en· W2498981201 on OpenAlexaff
Malcolm Campbell‐Verduyn

Bibliographic record

VenueBusiness and Politics · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNormativeRegulatory authorityPrimary authorityState (computer science)Public authorityIslamPrivate enterpriseMoral authoritySociologyPolitical sciencePublic relationsEconomicsLawPublic administrationFinanceMoral disengagement

Abstract

fetched live from OpenAlex

This article examines the “technology, information, and news corporations” (TINCs), a group of under-studied non-state actors to enhance understanding of the interplay between forms of private authority in times of crisis. Three interrelated arguments regarding the shifting private authority of leading UK- and US-based TINCs are presented. First, contributions to the period of economic instability that began in 2007 have destabilized the long-standing authority of Anglo-American firms including Bloomberg, Dow Jones, and Thomson Reuters. Second, through their involvement in two overtly normative niches of global finance, environmental and Islamic finance, these private actors have responded to contestations of their authority with an enhanced stress on moral authority since 2007. Third, a mere tinkering around with pre-crisis technical knowledge and a persistent reliance on liberal market values is likely to perpetuate rather than resolve the unstable authority of the leading TINCs. Based on an original analysis of primary documents and interviews undertaken with industry participants, this article contributes to existing literature analyzing the changing nature of private authority by revealing limits to shifts and combinations between its moral and technical forms.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.210

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.210
Teacher spread0.195 · 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 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

Citations7
Published2016
Admission routes1
Has abstractyes

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