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Record W2574951010 · doi:10.1108/sbm-11-2014-0046

Leading under pressure: evaluating the decision-making style of NHL coaches

2017· article· en· W2574951010 on OpenAlexaff
Kim Trottier

Bibliographic record

VenueSport Business and Management An International Journal · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHeuristicsIntuitionPsychologyAmateurPerceptionEliteExploratory researchApplied psychologyComputer sciencePolitical scienceSociology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to establish the optimal decision-making style in a fast-paced, complex, and dynamic environment. Design/methodology/approach Three decision-making attributes are explored: the use of intuition vs analysis, the proclivity to heuristics, and susceptibility to bias. The intuition/analysis is tested with a questionnaire that has been validated in prior research, while information on the two other dimensions is from an exploratory survey designed for this purpose. Responses to the survey questions provide some insight into the differential decision-making style of elite NHL hockey coaches’ vis-à-vis amateur coaches and news reporters. Findings The data suggest elite decision makers have no preference for intuitive or analytical settings, but exhibit a significantly higher perception of their ability to perform in both. While current literature shows sports athletes to be more intuitive, it appears coaches excel on the analytical dimension instead. This study finds that while elite hockey coaches have fewer biases overall, they tend in particular to be overly optimistic in comparison to amateur coaches and news reporters. Research limitations/implications The main limitation in this paper is that the survey on heuristics and biases is exploratory, making these results less robust than the findings on intuition and analysis. Originality/value This paper is first to extend the decision-making literature to coaches, and among few papers that obtain insights from NHL coaches directly. The findings are likely to extend to corporate leadership as well, increasing the relevance of the results.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.072
GPT teacher head0.334
Teacher spread0.262 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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