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Record W4307989845 · doi:10.3390/ijerph192114219

What Is on Your Gig Radar? Toward a Hierarchical Structure of Coping

2022· review· en· W4307989845 on OpenAlexaff
Samira A. Sariraei, Denis Chênevert, Christian Vandenberghe

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typereview
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCoping (psychology)PsychologyAutonomyCompetence (human resources)Applied psychologySocial psychologyClinical psychology

Abstract

fetched live from OpenAlex

Digitalized independent workers, known as gig workers, have been shown to work under high-pressure, with a lack of autonomy, a lack of feedback and perceived competence, and a high level of isolation. We conducted a literature review to investigate how gig workers cope with these sources of stress. We identified primary sources of psychological stress in gig work and the main strategies used by workers for coping with them. We show that focusing solely on identifying coping strategies depicts a fragmented literature, making it impossible to compare, link, or aggregate findings. We suggest a radar classification of coping based on the motivational action theory of coping and self-determination theory that defines coping as a process to adapt to the environment and maintain well-being. We argue that this framework is both relevant and necessary for developing research on gig-worker coping.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.177
GPT teacher head0.450
Teacher spread0.273 · 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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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