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Record W2286925039 · doi:10.20381/ruor-6768

Essays on the Economics of Sleep Time and Work Stress

2014· dissertation· en· W2286925039 on OpenAlexaboutno aff
Golnaz Sedigh

Bibliographic record

VenueuO Research (University of Ottawa) · 2014
Typedissertation
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsSleep (system call)Work (physics)Stress (linguistics)PsychologyCognitive psychologyComputer scienceEngineeringMechanical engineeringPhilosophyLinguistics

Abstract

fetched live from OpenAlex

This thesis consists of three essays on the economics of sleep time and work stress. The first essay, “the impact of economic factors on sleep: the role of insomnia”, discusses the role played by insomnia on the link between economic variables and sleep time. Insomnia is a common phenomenon experienced by many Canadians. This paper uses the Canadian General Social Survey (GSS) 2005 to investigate the effect of economic factors on the sleep time of the labour force. It replicates previous work by Biddle and Hamermesh (1990) and then extends this work to look at the role played by insomnia on the link between economic variables and sleep time. The paper concludes that the presence of sleep problems can significantly change the impact of economic determinants such as wage and education on sleep time. This paper finds that a 10 percent increase in the wage rate decreases sleep time by almost 20 minutes per week for non-insomniacs while an increase in the wage rate does not have any impact on sleep time for insomniacs. In fact, the link between wage and sleep time appears to be broken for insomniacs as they do not want to, or cannot, sacrifice their sleep time in order to have more money in their pockets. The second essay, “sleep time and wages: the role of chronic diseases and work environment”, examines the role played by chronic diseases and work environment on the link between economic variables and sleep time. This paper, which expands on the work of the first essay, uses the Canadian Community Health Survey (CCHS) 2001 to investigate the roles of insomnia, chronic diseases and stressful work environments on the link between the wage rate and sleep time. Whereas Biddle and Hamermesh (1990) report that individuals sleep 14 minutes less per week as a result of a 10% increase in the wage rate, I find that this number increases to 30 minutes for individuals without sleep problems while it is zero for insomniacs. Moreover, the impact of wages on sleep time is even more pronounced – more than 60 minutes per week - once account is taken of health conditions and of the work environment. Interestingly, these health and environmental effects are in addition to their impact on insomnia: in other words, individuals with chronic health problems who are not insomniacs do not respond to an increase in the wage rate by reducing their sleep time. This means that the actual impact of wages on sleep time for those who do not suffer from these conditions is much more important than originally reported by Biddle and Hamermesh (1990). The third essay, “are Québecers more stressed out at work than others? An investigation into the differences between Québec and the Rest of Canada in the level of work stress” discusses the level of stress experienced by workers in Canada. Work stress has a large socio-economic impact: it affects worker absenteeism, productivity, and family life. Psychological health problems including stress at workplace are an important issue in Canada. Using nine cycles spanning twelve years of the Canadian Community Health Survey (CCHS), I find that the level of work stress in Québec is much higher than in any other province. In Québec, 40% of the population report having quite a bit or extremely stressful jobs. In the other provinces, this number is much smaller, in the order of 30% in Ontario, Alberta, Manitoba and British Columbia, and even lower in the Atlantic Provinces. I find that Québec still has a higher level of reported work stress even after controlling for the main determinants of work stress: income, education, health, age, gender, marital status, children and work environment. Unionization rate and unemployment rate in the province do not seem to matter. However, I find that immigrants in Québec have less work stress than native-born Francophones. Also, Francophones in Québec and elsewhere have higher levels of work stress than Anglophones and Allophones. A body of literature has examined the subject of work stress, and while it has been noted by a few authors (Bordeleau and Traoré, 2007 and Lesage et al., 2010) that Québec is different; a thorough analysis of the causes of this phenomenon needs to be done. This paper estimates regression models that include a large number of factors such as age, gender, marital status, census metropolitan area (CMA), urban, immigrants, having young children, household type, living arrangement, mother tongue, language of conversation, race, education, income, working hours, part time job, health, physical activity, type of smoker, type of drinker, sense of belonging to community, provincial unionization rate and provincial unemployment rate to examine why there may be a consistent and persistent different between those who reside in Québec relative to the rest of Canada. I find that, even after controlling for those factors, work stress is still higher in Québec. This study suggests that differences in the legal systems and in cultures may be some of the reasons of the differences between Québec and the rest of Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2014
Admission routes1
Has abstractyes

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