Ten years of conflict management studies: themes, concepts and relationships
Bibliographic record
Abstract
Purpose The purpose of this paper is to map the intellectual structure of conflict management studies and to investigate the key themes, concepts, and their relationships of conflict management literature in the past decade. Design/methodology/approach Citation and co‐citation analysis and social network analysis were used to trace the development path of conflict management research. The data were collected by searching the SSCI databases, based on 556 journal articles which were published between 1997 and 2006, and their cited references were analyzed and profiled. Findings The paper shows that conflict management literature focuses on three key themes: workplace conflict and conflict management styles, cultural differences in conflict management, and conflict management in practice. In addition, research on group conflict and work performance has gained momentum in recent years. Originality/value The intellectual structure of conflict management literature has received little attention in spite that a large number of studies have been done on conflict management. This paper will expose researchers to a new way of profiling key themes and their relationships in conflict management area, which will help academia and practitioners understand better contemporary conflict management studies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.024 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".