Presenteeism and absenteeism: Differentiated understanding of related phenomena.
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
In the past it was assumed that work attendance equated to performance. It now appears that health-related loss of productivity can be traced equally to workers showing up at work as well as to workers choosing not to. Presenteeism in the workplace, showing up for work while sick, seems now more prevalent than absenteeism. These findings are forcing organizations to reconsider their approaches regarding regular work attendance. Given this, and echoing recommendations in the literature, this study seeks to identify the main behavioral correlates of presenteeism and absenteeism in the workplace. Comparative analysis of the data from a representative sample of executives from the Public Service of Canada enables us to draw a unique picture of presenteeism and absenteeism with regards not only to the impacts of health disorders but also to the demographic, organizational, and individual factors involved. Results provide a better understanding of the similarities and differences between these phenomena, and more specifically, of the differentiated influence of certain variables. These findings provide food for thought and may pave the way to the development of new organizational measures designed to manage absenteeism without creating presenteeism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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