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Record W2159766125 · doi:10.5267/j.msl.2015.4.004

The relationship between principals’ reward power and their conflict management styles based on Thomas–Kilmann conflict mode instrument

2015· article· en· W2159766125 on OpenAlexvenueno aff
Arash Riasi, Nasrin Asadzadeh

Bibliographic record

VenueManagement Science Letters · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsnot available
Fundersnot available
KeywordsConflict managementPsychologyPower (physics)Management stylesSocial psychologyStyle (visual arts)Leadership styleOrganizational conflictMode (computer interface)Applied psychologyPolitical sciencePublic relationsSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

This paper studies the relationship between principals' reward power and their conflict management styles.The five conflict management styles that we use in this study are based on Thomas-Kilmann Conflict Mode Instrument and include accommodating, avoiding, collaborating, competing, and compromising styles.This study can be classified as a regression analysis and is a descriptive study.Our statistical society for this research included all principals of high schools located in the city of Birjand.The results indicated that there was a significant relationship between principal's reward power and accommodating conflict management style.The results also revealed that there was no significant relationship between principals' reward power and the other four conflict management styles.

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)0.016
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
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.317
Teacher spread0.240 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

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