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Record W3205017079 · doi:10.1177/23792981211054848

Sorting It Out: Identifying and Addressing Conflicts and Business Ethics in Global Value Networks

2021· article· en· W3205017079 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

VenueManagement Teaching Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare Facilities Design and Sustainability
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCard sortingValue (mathematics)Task (project management)DilemmasortBusiness ethicsKnowledge managementCompromiseEthical dilemmaPublic relationsProduct (mathematics)SociologyEngineering ethicsComputer sciencePolitical scienceManagementEngineeringEpistemologySocial science

Abstract

fetched live from OpenAlex

Global value networks are often large, complex, and opaque. Understanding the relationships among stakeholders involved in these networks or organizations can be challenging. This card sort task provides an interactive way to engage participants in questioning the roles of stakeholders who are involved in a business ethics dilemma or an organizational product failure. This card sort task and discussion activity encourages participants to recognize that stakeholders may hold different knowledge, responsibility, or power; identify competing, conflicting, or complementary interests across stakeholders; articulate logical arguments; and engage in debate, compromise, and critical evaluation. This technique has been used successfully with undergraduate and postgraduate business, management, and social science students and is suitable for in-person and remote classes.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.175
GPT teacher head0.448
Teacher spread0.274 · 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