A Study of Generational Conflicts in the Workplace
Bibliographic record
Abstract
This article reviews research around generational differences and examines the causality between these differences and conflicts usually happening at the workplace. The conflicts can be defined as value-based, behaviour-based, or identity-based. These generational differences also affect managers’ strategies when dealing with conflicts at work. Morton Deutsch’s theory of cooperation and competition is often used for organisations to understand the nature of conflicts, and the Conflict Process Model can be used to examine how conflicts can evolve. Studies show that once a generational conflict is identified and understood, organizations can mitigate and resolve the conflict by developing mentorship between the parties involved to embrace generational diversity. Various components of the HR activities should also be altered to adapt generational differences for an organization to attract and retain talents. As events and developments that caused generational differences are chronological, conflicts that could arise from the reactions by different generations to the future of work leaping through the recent Covid-19 pandemic should be prepared. However, some studies raised debate about the causality between generations and behavioural characteristics at work and argued the necessity of managing conflicts caused by generational differences, raising concerns that attributing conflicts to generational differences potentially oversimplifies the problems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".