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Record W4225898123 · doi:10.1177/00076503221084647

Alternative Organizations as Systems Hijacking: The Commercial Trust as a Thought Experiment

2022· article· en· W4225898123 on OpenAlexafffund
Heather Hachigian

Bibliographic record

VenueBusiness & Society · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research Council of CanadaVancouver Foundation
KeywordsAnalogyCorporate governanceProcess (computing)Context (archaeology)Social systemReflection (computer programming)BusinessSociologyPublic relationsEconomicsComputer scienceManagementEpistemologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The COVID-19 crisis has renewed interest in alternative forms of organizing business and investment but our understanding of how these organizations can transform social systems is limited. The purpose of this article is to contribute to this understanding. In the context of one of the greatest transfers of wealth in global retail history that could see unprecedented numbers of businesses close or sold to distant, private interests, the article performs a thought experiment using the analogy of a commercial trust to encourage new ideas and critical reflection on community wealth building. The article introduces systems hijacking-a process of leveraging incumbent forms and systems in which they are embedded for new purposes-as an analytically useful concept for understanding how alternative organizations can transform social systems. The article finds organizational governance is necessary to transcend structural deficiencies in inherited or borrowed forms to make way for transformation.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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 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

Citations6
Published2022
Admission routes2
Has abstractyes

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