Career Experiences of Non-Profit Organization (NPO) Employees: An Exploration Research of NPO Employees’ Work Meaningfulness and Work-life Balance.
Bibliographic record
Abstract
With the recent challenges societies have had to face, including natural disasters and wars, non-profit organizations and the aid they provide, by the means of a mixed workforce: both local and expatriates, have become even more prevalent. However, they are facing a “talent war” as they are struggling to retain and attract new employees. Mega events, including COVID-19, have shed additional light on certain elements related to one’s well-being, mainly one’s work-life balance and work-meaningfulness, making them more valuable to employees, thus important to organizations wanting to limit turnover rates. These working experiences are seemingly still lacking understanding across the non-profit industry due to scarce research on the topic. This micro-levelled qualitative study will further explore the working experiences of non-profit employees, locals and expatriates, across a variety of non-profit organizations. 21 participants were recruited across 5 countries and their interviews were thematically analysed. Findings show that non-profit employees have an overall good sense of work meaningfulness. Work-life balance was found satisfactory by interviewees’ self-perceptions but was objectively more conflicting. Expatriates were found to have an overwhelming greater sense of work-meaningfulness compared to locally employed workforce which was seemingly associated with greater work-family conflicts. This research contributes not only to the current non-profit literature but also to practitioners, by bringing additional insights into the working experiences held across the non-profit industry as well as those that employees enjoy experiencing. Future research should focus on further establishing quantitatively this research’s findings.
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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 | 0.004 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".