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Record W2172069765 · doi:10.1123/tsp.22.3.336

High Altitude Climbers as Ethnomethodologists Making Sense of Cognitive Dissonance: Ethnographic Insights from an Attempt to Scale Mt. Everest

2008· article· en· W2172069765 on OpenAlexaff
Shaunna Burke, Andrew C. Sparkes, Jacquelyn Allen‐Collinson

Bibliographic record

VenueThe Sport Psychologist · 2008
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCognitive dissonanceReflexivityPsychologyCognitionSocial psychologyEthnographySelf-perception theoryScale (ratio)Cognitive psychologySociologyGeographyAnthropologyCartography

Abstract

fetched live from OpenAlex

This ethnographic study examined how a group of high altitude climbers ( N = 6) drew on ethnomethodological principles (the documentary method of interpretation, reflexivity, indexicality, and membership) to interpret their experiences of cognitive dissonance during an attempt to scale Mt. Everest. Data were collected via participant observation, interviews, and a field diary. Each data source was subjected to a content mode of analysis. Results revealed how cognitive dissonance reduction is accomplished from within the interaction between a pattern of self-justification and self-inconsistencies; how the reflexive nature of cognitive dissonance is experienced; how specific features of the setting are inextricably linked to the cognitive dissonance experience; and how climbers draw upon a shared stock of knowledge in their experiences with cognitive dissonance.

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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.011
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0010.002
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 head0.077
GPT teacher head0.394
Teacher spread0.317 · 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 designQualitative
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
Published2008
Admission routes1
Has abstractyes

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