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Record W2932024253

Exploring the Association between Empathy and Conflict Management Styles

2019· article· en· W2932024253 on OpenAlexaboutno aff
Chaiyaset Promsri

Bibliographic record

VenueAcademy of Social Science Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyConflict managementPsychologyAssociation (psychology)Style (visual arts)Social psychologyLeadership styleGovernment (linguistics)Management stylesApplied psychologyPolitical scienceSociologyPublic relationsPsychotherapistSocial scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

The main objective of this study was to examine the association between empathy and conflict management styles. Twenty graduate students in MBA program in a selected government university were distributed the survey questionnaire. Only seventeen students returned the questionnaire with completion. Empathy was measured by using the Toronto Empathy Questionnaire and conflict management styles were assessed based on modified version of conflict management questionnaire based on the concept of Thomas-Kilmann. Results indicated that graduate students had a medium level of empathy, and collaborating style was rated as the most favorable conflict management style for this group of students. In addition, Findings revealed the positive relationship between empathy and accommodating conflict style at a medium level (r = .531, p < .05). The recommendations for a further study and research implications were also proposed.

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)0.003
metaresearch head score (Gemma)0.019
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.093
GPT teacher head0.339
Teacher spread0.245 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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