Antecedents, Consequences, and Context of Employee Engagement in Nonprofit Organizations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The article draws on Kahn and Saks to examine the extent to which specific nonprofit antecedents affect engagement and how engagement mediates employee and organizational consequences. Our findings suggest that the consequences of job and organization engagement are the behavioral outcomes—job satisfaction, commitment, and organization citizenship behavior—that nonprofits consider as critical to their organization and the employees emphasize. Perhaps the strongest evidence of the impact of engagement is the finding that nonprofit employees are more likely to experience these consequences and less likely to have intention to quit even if antecedents such as job characteristics and value congruence are less likely. Consistent with the literature, we also found that value congruence is a major antecedent in the relationship between nonprofit employees, their jobs, and the organization. Our research presents one of the first findings that result from empirically validated measures of engagement in nonprofits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it