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Record W2122670974 · doi:10.1177/1046878105275454

Validating business gaming: Business game conformity with PIMS findings

2005· article· en· W2122670974 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

VenueSimulation & Gaming · 2005
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBusiness simulationConformityMarketingGame mechanicsProfit (economics)Business analysisBusiness modelComputer scienceBusinessPsychologyKnowledge managementEconomicsMicroeconomicsMultimediaSocial psychology

Abstract

fetched live from OpenAlex

Business games have been in use in university classes in North American for 50 years. A concern over this time has been whether or not participation in such games is a meaningful experience. The merit of business games has been examined by looking at what is taught by games, comparing games to other teaching approaches, and assessing the external and internal validity of games. This article examines another approach to assessing business games. The performance outcomes of more than 2,000 students operating 717 simulation companies in 154 industries has been examined to determine if these outcomes conform to real-world business firm outcomes as reported in the ongoing PIMS (Profit Impact of Marketing Strategies) project. The findings from this research suggest once again that business simulation games are a valid teaching tool.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.335
Teacher spread0.299 · 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