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Record W1564622940 · doi:10.1108/ijshe-06-2014-0084

Do, but don’t tell

2015· article· en· W1564622940 on OpenAlexaboutno aff
Timothy A. Hart, Corey Fox, Kenneth F. Ede, John Korstad

Bibliographic record

VenueInternational Journal of Sustainability in Higher Education · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)OriginalitySustainabilityValue (mathematics)Higher educationPublic relationsBusiness educationBusinessMedical educationSociologyPolitical scienceComputer scienceQualitative researchMedicineGeography

Abstract

fetched live from OpenAlex

Purpose – The purpose of this study is to investigate the degree to which business schools, in particular MBA programs, have developed academic programs and centers specifically focused on corporate social responsibility and sustainability (CSRS) and, for those that have, promote them on their Web sites. The instruction of CSRS in institutions of higher education is increasing worldwide. The extent to which US MBA programs have developed academic programs and centers focused on CSRS could potentially be a way for business schools to distinguish themselves from other schools. Design/methodology/approach – The authors use a Web-based search of the Web sites of the top-100 US MBA programs to ascertain the extent to which they have developed CSRS-related academic programs and centers. They then look specifically at the full-time MBA main Web page to ascertain to what extent these programs promote CSRS material. Findings – The results suggest that schools in the top quarter and bottom quarter, as well as private schools, are more likely to have CSRS academic programs and centers. The authors also find that very few full-time MBA programs promote CSRS on their main MBA Web pages. Originality/value – This study is unique in its focus on the top-100 US MBA programs and the collection of primary data directly from their Web sites. Additionally, a summary of the data gathered from the MBA programs is provided in Table I of the study.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.050
GPT teacher head0.338
Teacher spread0.288 · 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 designObservational
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

Citations25
Published2015
Admission routes1
Has abstractyes

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