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Record W2066620029 · doi:10.3357/asem.1623.2010

Conflict-Handling Mode Scores of Three Crews Before and After a 264-Day Spaceflight Simulation

2010· article· en· W2066620029 on OpenAlexaff
Rachel Kass, J.R. Kass, Heidi Binder, Norbert Kraft

Bibliographic record

VenueAviation Space and Environmental Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsConcordia University
FundersJapan Aerospace Exploration Agency
KeywordsCrewInterpersonal communicationPsychologyIsolation (microbiology)SpaceflightGovernment (linguistics)Space (punctuation)Mode (computer interface)Social psychologyApplied psychologyAeronauticsEngineeringComputer science

Abstract

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INTRODUCTION: In both the Russian and U.S. space programs, crew safety and mission success have at times been jeopardized by critical incidents related to psychological, behavioral, and interpersonal aspects of crew performance. The modes used for handling interpersonal conflict may play a key role in such situations. METHODS: This study analyzed conflict-handling modes of three crews of four people each before and after a 264-d spaceflight simulation that was conducted in Russia in 1999-2000. Conflict was defined as a situation in which the concerns of two or more individuals appeared to be incompatible. Participants were assessed using the Thomas-Kilmann Conflict Mode Instrument, which uses 30 forced-choice items to produce scores for five modes of conflict handling. Results were compared to norms developed using managers at middle and upper levels of business and government. RESULTS: Both before and after isolation, average scores for all crews were above 75% for Accommodating, below 25% for Collaborating, and within the middle 50% for Competing, Avoiding, and Compromising. Statistical analyses showed no significant difference between the crews and no statistically significant shift from pre- to post-isolation. DISCUSSION: A crew predisposition to use Accommodating most and Collaborating least may be practical in experimental settings, but is less likely to be useful in resolving conflicts within or between crews on actual flights. Given that interpersonal conflicts exist in any environment, crews in future space missions might benefit from training in conflict management skills.

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)0.000
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 score0.246
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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