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Record W2993355762 · doi:10.46743/2160-3715/2019.3946

Work Related Paternal Absence among Petroleum Workers in Canada

2019· article· en· W2993355762 on OpenAlexaffabout
Simon Nuttgens, Emily M. Doyle, Jeff Chang

Bibliographic record

VenueThe Qualitative Report · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsAthabasca University
Fundersnot available
KeywordsInterviewWork (physics)Petroleum industryThematic analysisPetroleumQualitative researchPsychologySociologyPolitical scienceEngineeringSocial scienceLaw

Abstract

fetched live from OpenAlex

Work-Related Parental Absence (WRPA) is common in contemporary family life. Industries such as aviation, fishing, logging, mining, and petroleum extraction all require the employee to work away from family from short to significant periods of time. In Canada’s petroleum industry, work schedules that involve parental absence are especially common. There has been ample research conducted on the impact of military deployment on families, some research on how mining families are impacted by WRPA, and a small amount of research on the effects of WRPA among offshore European petroleum workers and their families. However, there is no research currently available that investigates the impact of WRPA on Canadian oil and gas petroleum workers and their families. In this article, we share the results of a qualitative study that examined the experience of WRPA through interviewing 10 heterosexual couples. Use of Interpretive Phenomenological Analysis identified a tripartite thematic structure consisting of positive, negative, and neutral aspects of the WRPA experience, which in turn were shaped by specific adaptive strategies undertaken by families. The results of this research provide important insights into a common, yet poorly understood, lifestyle within the Canadian employment landscape.

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)0.005
metaresearch head score (Gemma)0.001
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 score0.207
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.373
Teacher spread0.328 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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