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Record W1976133323 · doi:10.1108/eb022913

CONCEPTUALIZING THE CONSTRUCT OF INTERPERSONAL CONFLICT

2004· article· en· W1976133323 on OpenAlexaff
Henri Barki, Jon Hartwick

Bibliographic record

VenueInternational Journal of Conflict Management · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsMcGill UniversityHEC Montréal
Fundersnot available
KeywordsConceptualizationInterpersonal communicationConstruct (python library)PsychologyOperationalizationSocial psychologyTypologyInterdependenceEpistemologySociologyComputer science

Abstract

fetched live from OpenAlex

The lack of a clear conceptualization and operationalization of the construct of interpersonal conflict makes it difficult to compare the results of different studies and hinders the accumulation of knowledge in the conflict domain. Defining interpersonal conflict as a dynamic process that occurs between interdependent parties as they experience negative emotional reactions to perceived disagreements and interference with the attainment of their goals, the present paper presents a two-dimensional framework and a typology of interpersonal conflict that incorporates previous conceptualizations of the construct. The first dimension of the framework identifies three properties generally associated with conflict situations: disagreement, negative emotion, and interference. The framework's second dimension identifies two targets of interpersonal conflict encountered in organizational settings: task and interpersonal relationship. Based on this framework, the paper highlights several shortcomings of current conceptualizations and operationalizations of interpersonal conflict in the organizational literature, and provides suggestions for their remedy.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0030.011
Scholarly communication0.0080.009
Open science0.0030.007
Research integrity0.0020.004
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 head0.033
GPT teacher head0.337
Teacher spread0.304 · 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 designTheoretical or conceptual
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

Citations464
Published2004
Admission routes1
Has abstractyes

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