LOOKING AT THE FACTORS AFFECTING CONFLICT IN ORGANIZATION: AN UNDERSTUDY LEADING TO A CONCEPTUAL MODEL
Bibliographic record
Abstract
The purpose of this paper is to present and group an array of factors that are affecting employee related conflicts within organizations. Understanding sources of conflict has been a subject matter that raises interest from academics, professionals and managers alike. Extant research has shown that conflict is an essential characteristic of learning organizations and a certain level of it should be tolerated as it is often the medium of knowledge transfer to and from individuals. The difficulty arises when managers do not understand, or are able to identify, the sources, the clusters and the ensuing factors generating conflict and as such their efforts to choose between resolution and managing conflict are rendered inutile and without focus. The identification and grouping or such factors becomes an imperative and needs a general framework that could be applied and adapted to each organization regardless of industry. We therefore identify the following clusters of factors affecting conflict: environmental, individual and firm related factors based on which we issue propositions and managerial implications
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".