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Record W4381610790 · doi:10.1111/capa.12520

Government of Canada's teleworking and hybrid policies in the aftermath of the COVID‐19 pandemic

2023· article· en· W4381610790 on OpenAlexafffundabout
Éric Champagne, Olivier Choinière, Aracelly Denise Granja

Bibliographic record

VenueCanadian Public Administration · 2023
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité du Québec à RimouskiUniversity of OttawaInstitute on Governance
FundersGovernment of Canada
KeywordsCoronavirus disease 2019 (COVID-19)Government (linguistics)PandemicWork (physics)Public policyPublic sectorPublic administrationPolitical science2019-20 coronavirus outbreakHistorical institutionalismInstitutionalismEconomic growthEconomicsPoliticsEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract This article analyzes the evolution of teleworking and hybrid work policies in the public sector over the last two decades. It focuses on the Government of Canada, concentrating on the paradigmatic shifts brought about by COVID‐19, particularly the impact on the development of teleworking and the transformation of the workplace into a hybrid model. Based on a historical neo‐institutionalism approach, this article suggests that the pandemic has propelled the expansion of telework reforms, becoming a key driver in altering the application of both telework and hybrid policies. However, this article argues that, despite the general recognition in the effectiveness of telework and hybrid policies, there are still headways to be made, predominantly because there is still disagreement as to how these policies should be defined and ultimately applied in the federal public sector.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.555
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.081
GPT teacher head0.357
Teacher spread0.276 · 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

Citations23
Published2023
Admission routes3
Has abstractyes

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