Work-Related Flow in Contrast to Either Happiness or PERMA Factors for Human Resources Management Development of Career Sustainability
Bibliographic record
Abstract
In promoting career sustainability, psychological theories historically have informed human resource management (HRM) development—three assessment directions are among them: work-related flow, happiness promotion, and appraising PERMA (Positive Emotions, Engagement, Relationships, Meaning, and Accomplishment) factors. Csikszentmihalyi’s work-related flow represents an optimally challenging work-related process. Happiness promotion strives to maintain a pleased satisfaction with the current experience. PERMA represents measurable positive psychological factors constituting well-being. Reliable and validated, the experience of flow has been found to determine career sustainability in contrast to the more often investigated happiness ascertainment or identifying PERMA factors. Career sustainability research to inform HRM development is in its infancy. Therefore, publishers’ commitment to sustainability provides integrity. Given MDPI’s uniquely founding sustainability concern, its journal articles were searched with the keywords “flow, Csikszentmihalyi, work”, excluding those pertaining to education, health, leisure, marketing, non-workers, and spirituality, to determine the utilization of work-related flow to achieve career sustainability. Of the 628 returns, 28 reports were included for potential assessment. Current studies on Csikszentmihalyi’s work-related flow ultimately represented three results. These provide insight into successful, positive methods to develop career sustainability. Consequently, HRM is advised to investigate practices for assessing and encouraging employees’ engagement with work-related flow with the aim of ensuring career sustainability.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".