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Record W2046532942 · doi:10.1108/13522750210414508

Participatory group observation – a tool to analyze strategic decision making

2002· article· en· W2046532942 on OpenAlexaff
Christine Vallaster, Oliver Koll

Bibliographic record

VenueQualitative Market Research An International Journal · 2002
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsGroup decision-makingDivergence (linguistics)CognitionKnowledge managementRealismInterpersonal communicationGroup (periodic table)Management scienceConvergence (economics)Citizen journalismComputer scienceStrategic alignmentPsychologyStrategic managementStrategic planningProcess managementSocial psychologyBusinessStrategic financial managementEngineeringMarketingEconomicsEpistemology

Abstract

fetched live from OpenAlex

Group decisions have taken a prominent part in strategic decision making but managerial research still lacks techniques to study these interpersonal processes comprehensively. Assuming that efficient decision making depends on shared cognitive structures within groups, an approach to analyze these structures and the affective and communicative dimensions causing convergence/divergence of individual cognitions is introduced. Suitable methods to study these variables are discussed and applied in an actual strategic decision to be made by a management team. The method shows a high degree of realism and preciseness in analyzing strategic group decisions.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.414
GPT teacher head0.569
Teacher spread0.154 · 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.

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

Citations22
Published2002
Admission routes1
Has abstractyes

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