MétaCan
Menu
Back to cohort
Record W2074800566 · doi:10.7771/2327-2937.1043

Motivation in Extreme Environments: A Case Study of Polar Explorer Pen

2006· article· en· W2074800566 on OpenAlexaboutno aff
Juliette C. Lloyd, Michael J. Apter

Bibliographic record

VenueHuman performance in extreme environments · 2006
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)AthletesPsychologyQualitative analysisComputer scienceQualitative researchSociologySocial science

Abstract

fetched live from OpenAlex

This study documents the motives of a polar explorer, Pen Hadow, during the period of a 64-day solo expedition in which he skied, without resupply by aircraft, from Canada to the North Geographic Pole. The framework of reversal theory (Apter, 1982) was used to provide a systematic and comprehensive structure for studying such motivation in an extreme environment. Quantitative data were obtained by using the Apter Record of Motivational States. Qualitative data came from interviews structured in terms of reversal theory. The main result was that the explorer needed at different times to call upon all the eight motivational states identified by reversal theory rather than being subject to only the one or two most obvious ones. The telic and autic states were the two that occurred most frequently. Implications for would-be explorers, and for extreme athletes and their coaches, are indicated.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.010
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0030.002
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.106
GPT teacher head0.283
Teacher spread0.177 · 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

Citations10
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueHuman performance in extreme environmentsSame topicAdventure Sports and Sensation SeekingFrench-language works237,207