GONE FISHING! REPORTED SICKNESS ABSENTEEISM AND THE WEATHER
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
A fundamental challenge in informing employer–employee agency problems is measuring employee shirking activity. We identify the propensity of employees to misreport health in order to exploit favorable weather by linking Canadian weather data and survey data on short‐term spells of sickness absenteeism among indoor workers during the non‐winter months. The results point to a clear tendency for reported sickness absenteeism to rise with the recreational quality of the weather. Comparing across workers suggests larger marginal weather effects where shirking costs are higher, which we show is consistent with employees' marginal utility of outdoor leisure increasing in the interaction of their health and weather quality. We discuss the implications of our findings for flexible vacation policies and survey respondents' trust in the confidentiality guarantees of statistical agencies . ( JEL D82, I10, J22)
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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