Attendance dynamics at work: The antecedents and correlates of presenteeism, absenteeism, and productivity loss.
Bibliographic record
Abstract
Presenteeism is attending work when ill. This study examined the antecedents and correlates of presenteeism, absenteeism, and productivity loss attributed to presenteeism. Predictors included work context, personal characteristics, and work experiences. Business school graduates employed in a variety of work positions (N = 444) completed a Web-based survey. Presenteeism was positively associated with task significance, task interdependence, ease of replacement, and work to family conflict and negatively associated with neuroticism, equity, job security, internal health locus of control, and the perceived legitimacy of absence. Absenteeism was positively related to task significance, perceived absence legitimacy, and family to work conflict and negatively related to task interdependence and work to family conflict. Those high on neuroticism, the unconscientious, the job-insecure, those who viewed absence as more legitimate, and those experiencing work-family conflict reported more productivity loss. Overall, the results reveal the value of a behavioral approach to presenteeism over and above a strict medical model. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".