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Record W2092154567 · doi:10.2190/hs.40.1.a

Ensuring a Healthy and Productive Workforce: Comparing the Generosity of Paid Sick Day and Sick Leave Policies in 22 Countries

2010· review· en· W2092154567 on OpenAlexaffabout
Jody Heymann, Hye Jin Rho, John Schmitt, Alison Earle

Bibliographic record

VenueInternational Journal of Health Services · 2010
Typereview
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsSick leaveWorkforceWageGenerosityLabour economicsWork (physics)Demographic economicsBusinessMedicineEconomicsEconomic growthPolitical science

Abstract

fetched live from OpenAlex

National paid sick day and paid sick leave policies are compared in 22 countries ranked highly in terms of economic and human development. The authors calculate the financial support available to workers facing two different kinds of health problems: a case of the flu that requires missing 5 days of work, and a cancer treatment that requires 50 days of absence. Only 3 countries--the United States, Canada, and Japan--have no national policy requiring employers to provide paid sick days for workers who need to miss 5 days of work to recover from the flu. Eleven countries guarantee workers earning the national median wage full pay for all 5 days. In Ireland and the United Kingdom, the full-time equivalent benefits are more generous for low-wage workers than for workers earning the national median. The United States is the only country that does not provide paid sick leave for a worker undergoing a 50-day cancer treatment. Luxembourg and Norway provide 50 full-time equivalent working days of leave, while New Zealand provides the least, at 5 days. In 6 countries, paid sick leave benefits are more generous for low-wage workers than for median-wage workers.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.877
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.096
GPT teacher head0.460
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations80
Published2010
Admission routes2
Has abstractyes

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