The Impact of Flexible Working Arrangements on Millennials: A Conceptual Analysis
Bibliographic record
Abstract
Recent statistics show that millennials make up about 40% of the employees struggling with mental health issues at the workplace in Malaysia.Concurrently, inflexible work schedules have been listed as one of the work place hazards in the National Standard of Canada for Psychological Health and Safety in the workplace.Hence, as millennials will constitute a major part of the global workforce in years to come, it is crucial to study the impact of flexible working arrangements on this category of employees.As flexible working arrangements (FWAs) provide a degree of control to the employees to decide their work arrangements in terms of time, place and method of working, it inadvertently allows an increase in autonomy of the employees.This conceptual paper first deliberates how flexible working arrangements may improve well-being and productivity of millennials since this generation values autonomy more than the previous generations.By using Self-Determination Theory at the workplace, this paper describes how flexible working arrangements (FWAs) support the need for autonomy among millennials, leading to improved well-being and productivity.Arguably, this paper proposes autonomy to be the mediator that links flexible working arrangements (FWAs), well-being and productivity.Finally, a theoretical framework is proposed for future research.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".