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Record W2073093839 · doi:10.1111/1467-8608.00245

Commerce with a conscience: corporate control and academic investment

2001· article· en· W2073093839 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBusiness Ethics A European Review · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsFiduciaryPublic relationsDutyInvestment (military)Higher educationDuty of loyaltyAutonomyControl (management)CompromisePower (physics)Construct (python library)Corporate governanceOrder (exchange)AccountingBusinessPolitical scienceEconomicsManagementLawFinancePolitics

Abstract

fetched live from OpenAlex

Corporations have been investing in academia to an extent that could be classified as a corporate takeover of universities. Intra‐university critics see this as an ethical problem, because of the degree of business control over university policies and decisions which accompanies the funding. University critics rarely suggest that the corporate funding be given up, returned, or even limited. What they protest against is corporate control, which they see as threatening university autonomy, and as inimical to the public good. Multi‐university conferences have been held focusing on this problem, and the most serious solution proposed thus far is to construct a relevant code of ethics regulating and limiting corporate involvement, through standards and guidelines which corporations will then have to subscribe to, in order to fund universities. However, there is a conflict of interest here. Universities have a public trust and a fiduciary duty not to compromise education. This implies a covenant not to cede power to outside interests, not to use university resources, or faculty and students, as a means to an educationally irrelevant end. Universities cannot sell out. However, it seems equally dishonest not to offer their students a well‐funded first‐rate, quality education in applied fields with current skills, maximum research opportunity, and the corporate ties that would allow them to obtain jobs. We examine three cases showing errors made by universities in ceding control to corporate investment, and draw some policy conclusions.

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.

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)0.022
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.622
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.490
GPT teacher head0.443
Teacher spread0.046 · 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