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Record W241122446

A Proven Way to Incorporate Catholic Social Thought in Business School Curricula: Teaching Two Approaches to Management in the Classroom

2013· article· en· W241122446 on OpenAlexaff
Bruno Dyck

Bibliographic record

VenueJournal of Catholic higher education · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicCatholicism and Religious Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMainstreamCurriculumIndividualismMaterialismBusiness educationSociologyPhilosophy of businessCatholic social teachingBusiness relationship managementPedagogyBusiness analysisPublic relationsEngineering ethicsBusiness modelMarketingHigher educationEpistemologyPolitical scienceBusinessElectronic businessLawEngineering
DOInot available

Abstract

fetched live from OpenAlex

Widespread agreement suggests that it is appropriate and desirable to develop and teach business theory and practice consistent with Catholic social teaching (CST) in Catholic business schools. Such a curriculum would cover the same mainstream material taught in other business schools, but then offer a CST approach to business that can be characterized by its relative de-emphasis on both materialism (e.g., business is not solely or primarily about maximizing financial well-being) and individualism (e.g., business should emphasize the common good rather than merely self-interests, especially of owners). Research shows that teaching management theory and practice consistent with CST alongside mainstream management theory (1) reverses the tendency for business students to become increasingly materialistic and individualistic; (2) enhances students’ critical thinking; and (3) enhances students’ ethical thinking. This article describes how a CST approach differs from a mainstream approach to management, accounting, finance, and marketing. Implications are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0040.003
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.060
GPT teacher head0.281
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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
Published2013
Admission routes1
Has abstractyes

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