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Record W2522432789

Into the mix: Personality processes and group dynamics in sport and exercise

2014· book-chapter· en· W2522432789 on OpenAlexaff
Mark R. Beauchamp, Ben Jackson, David Lavallee

Bibliographic record

VenueStirling Online Research Repository (University of Stirling) · 2014
Typebook-chapter
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGroup dynamicGroup (periodic table)Dynamics (music)PsychologyPersonalitySocial psychologyApplied psychologyChemistryPedagogy
DOInot available

Abstract

fetched live from OpenAlex

First paragraph: The importance of understanding, and attending to, the diverse personalities that comprise groups and teams has a rich history in social psychology. Kurt Lewin (1), who is generally regarded as the founding father of the field of ‘group dynamics’, noted that “in social research the experimenter has to take into consideration such factors as the personality of individual members” (p. 9). Just over three decades after Lewin’s seminal paper, another prominent group dynamics theorist, Marvin Shaw (2), similarly asserted that “personality characteristics of group members play an important role in determining their behavior in groups. The magnitude of the effect of any given characteristic is small but taken together the consequences for group processes are of major significance” (p. 208).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.037
GPT teacher head0.307
Teacher spread0.269 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

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