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Record W3107772852

Perceived impact of rotating shift work on health and wellbeing among underground workers

2019· dissertation· en· W3107772852 on OpenAlexaboutno aff
Chelsea V. Villeneuve

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2019
Typedissertation
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsnot available
Fundersnot available
KeywordsShift workWork (physics)PsychologyEnvironmental healthApplied psychologyEngineeringMedicinePsychiatryMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Workers in the mining industry are exposed to several risks and hazards in the
\nunderground environment. Shift work is a common working arrangement in the mining industry
\nand is associated with many adverse health outcomes. In Canada, there is limited research
\nbetween rotating shift work in the minerals industry and the effects on health and wellbeing of
\nworkers, especially utilizing a qualitative design. This thesis aimed to understand the impact of
\nrotating shift work on perceived health and wellbeing among some underground workers in
\nSudbury, Ontario.
\nThis qualitative descriptive study utilized individual, semistructured interviews with a
\nsample of underground workers (n = 12) employed in Sudbury, Ontario. Interviews were
\ndigitally recorded, transcribed verbatim, and analyzed using Braun and Clarke’s 2006 version of
\nthematic analysis. Participants in this study perceived both advantages and disadvantages of
\nworking on a rotating shift schedule in relation to their health and wellbeing. Final themes that
\nemerged from the data included: strong preference for the night shift, challenges associated with
\nimpact on personal wellbeing, advantages and disadvantages on work environment wellbeing,
\nbenefits and challenges of wellbeing external to work, strategies for coping with shift work,
\nfamily advantages, challenges with partner relationships, challenges and opportunities in
\nrelationships with children, and strategies used to protect family wellbeing. The findings of this
\nstudy may influence future research studies using a quantitative or mixed-method design, and
\nlarger samples.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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.

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
Published2019
Admission routes1
Has abstractyes

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