MétaCan
Menu
Back to cohort
Record W4285727705 · doi:10.21203/rs.3.rs-1821632/v1

The Effects of Teleworking in a Pandemic Context on the Well-Being of People with Disabilities: A Canadian Qualitative Study

2022· preprint· en· W4285727705 on OpenAlexaffabout
Alexandra Lecours, Marie‐Hélène Gilbert, Normand Boucher, Claude Vincent

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationUniversité LavalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsThematic analysisContext (archaeology)PandemicWork (physics)PsychologyCoronavirus disease 2019 (COVID-19)Well-beingQualitative researchApplied psychologyPublic relationsBusinessSociologyPolitical scienceMedicineEngineeringGeography

Abstract

fetched live from OpenAlex

Abstract The COVID-19 pandemic has led to numerous changes in work environments. Thousands of workers quickly found themselves having to telework without being prepared, which had consequences on their well-being. Authors proposed telework practices that promote the well-being of workers in a pandemic context, but less attention has been paid to consider the needs of disabled workers. Purpose . This study aimed to explore the effects of telework during the pandemic on the well-being of people with disabilities. Methods . Following an interpretive descriptive research design, interviews were conducted with 16 workers with disabilities (i.e., motor, or sensory). The data were analyzed using a thematic analysis strategy. Results . The results revealed 15 factors that influence the well-being of teleworkers with disabilities. These factors are related to interactions between three spheres of the worker's life: the individual, the organization, and the environment. Ten recommendations are proposed to consider the reality of disabled individuals in the telework practices. Conclusion . Given that telework has expanded since the onset of the COVID-19 pandemic and will likely continue to remain a widespread modality of work delivery, it becomes even more important to expand knowledge about it, to benefit the well-being of disabled teleworkers.

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)0.015
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.073
GPT teacher head0.432
Teacher spread0.360 · 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 designQualitative
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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueResearch SquareSame topicWork-Family Balance ChallengesFrench-language works237,207