MétaCan
Menu
Back to cohort
Record W4221082157 · doi:10.3390/ijerph19063284

International Comparison of Social Support Policies on Long-Term Care in Workplaces in Aging Societies

2022· article· en· W4221082157 on OpenAlexaboutno aff
Koji Kanda, Hirofumi Sakurazawa, Takahiko Yoshida

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
Fundersnot available
KeywordsSalarySocial supportBusinessWorking populationHealth careLong-term careOccupational safety and healthPopulation ageingPopulationDemographic economicsEconomic growthEnvironmental healthGerontologyMedicinePsychologyNursingPolitical scienceEconomics

Abstract

fetched live from OpenAlex

A decrease in the working-age population in aging societies causes a shortage of employees in workplaces due to long-term care (LTC) leave for family and relatives as well as longer working hours or overwork among those remaining in the workplace. We collected and analyzed literature and guidelines regarding social-support policies on LTC in workplaces in seven countries (Canada, France, Germany, Japan, Sweden, the UK, and the USA) to propose an effective way of occupational health support for those in need. Our analysis indicated the existence of a system that incorporates the public-assistance mechanism of providing unused paid leave to those in need. Additionally, recipients of informal care provided by employees tended to expand to non-family members under the current occupational health system. On the other hand, the health management of employees as informal caregivers remained neglected. Likewise, salary compensation and financial support for LTC-related leave need to be improved. In order to monitor and evaluate the progress and achievement of current legal occupational health systems and programs related to the social support of LTC among employees, the available national and/or state-based quantitative data should be comparable at the international level.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.431
Teacher spread0.375 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicIntergenerational Family Dynamics and CaregivingFrench-language works237,207