what helps and hinders workers in managing change
Bibliographic record
Abstract
This research responds to calls for increased understanding of workers' experiences of their work and work contexts. Informed by positive psychology, this study focused on a seldom‐studied subset of working individuals who self‐identified as doing well with change affecting their work and on strategies that helped or hindered them in doing well, factors that would have helped, and their experiences of change within the context of volatile and changing work situations. Using the enhanced critical incident technique methodology, the authors extracted 790 incidents from 45 participant interviews. These data were organized into the following 10 categories: support from friends and family, support from colleagues, support from professionals, personal attitudes/traits/emotional set, self‐care, internal framework and boundaries, taking action, skill/role competence, management style and work environment, and personal life changes/issues. The implications of these categories for research, theory, practice, and organizations are discussed.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".