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Record W3120041679 · doi:10.1080/25741292.2020.1864120

Gender and policy response to COVID-19 in Canada and Scotland

2021· article· en· W3120041679 on OpenAlexaffabout
Titilayo Soremi, Sefina Dogo

Bibliographic record

VenuePolicy Design and Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsSeneca Polytechnic
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicPoliticsPublic healthPolitical sciencePublic policy2019-20 coronavirus outbreakHealth policySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyPublic administrationHealth careMedicineLawNursingVirology

Abstract

fetched live from OpenAlex

Overcoming pandemics call for immediate and dedicated public health policy solutions. This study analyzes the public health policies introduced in the province of Ontario in Canada, and the country of Scotland in the United Kingdom, in a bid to address the COVID-19 pandemic. We focus on regional policy design by the key health policy decision makers and examine the influence of gender in the solutions introduced by these policy leaders. Drawing from the concept of feminist sociological institutionalism, we argue that that the solutions directed at curbing COVID-19, which was led by a female health minister in Ontario, and a female health secretary in Scotland, did not conform to gendered expectations. While the gendering of institutions is often streamlined to achieve gender equality and consider female issues, the study shows that undivided attention was dedicated to curbing COVID-19, without opportunistic interference and taking advantage of a political window.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0260.017
Scholarly communication0.0100.002
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.130
GPT teacher head0.436
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2021
Admission routes2
Has abstractyes

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