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Record W2081019586 · doi:10.1177/105382590803100107

Leadership Status Congruency and Cohesion in Outdoor Expedition Groups

2008· article· en· W2081019586 on OpenAlexaffabout
Mark Eys, Stephen D. Ritchie, Jim Little, Heather Slade, Bruce Oddson

Bibliographic record

VenueJournal of Experiential Education · 2008
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsLaurentian University
Fundersnot available
KeywordsGroup cohesivenessCohesion (chemistry)Social psychologyPsychologyAdventure educationOutdoor educationAdventurePerceptionPedagogy

Abstract

fetched live from OpenAlex

The purpose of the present study was to examine the relationship between status congruency and group cohesion in outdoor expedition groups in an educational setting. Specifically, three aspects of status congruency were assessed in relation to group cohesion in four adventure canoe groups. The groups participated in 2-week expeditions in the northern areas of the Canadian provinces of Ontario and Quebec. The participants were 32 upper-year undergraduate students enrolled in a central Canadian university (Mage = 22.41, SD = 2.43 years). Results indicated that (a) individuals who ranked themselves higher in the group's status hierarchy compared to where their peers ranked them had lower perceptions of their attraction to their group's social pursuits; (b) perceptions of group cohesion were greater when individuals occupying formal leadership positions were higher in the group's status ranking (i.e., greater congruency between formal and informal status hierarchies); and (c) individuals who were members of groups that had some level of consensus regarding status rankings perceived their groups to be more cohesive than those who were members of the group that had no consensus.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.357
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Experiential EducationSame topicSport Psychology and PerformanceFrench-language works237,207