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Record W4410818265 · doi:10.61959/vfpd1261e

COVID-19 IMPACTS: Couple Relationships in Canada

2020· report· en· W4410818265 on OpenAlexaboutno aff
Ana Fostik

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)GeographyVirologyBiologyMedicineOutbreakInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

When workplaces and schools closed in March 2020 to mitigate the spread of COVID-19, family life across Canada was profoundly affected. These unique circumstances increased pressure on couples, many of whom found themselves together 24/7 – sometimes with children – while quickly adapting their homes into shared workspaces and/or learning environments. In addition to ongoing uncertainties and anxieties related to the coronavirus itself, these sudden and major adjustments in work and family life led some to wonder whether the impacts of COVID-19 might lead to increased rates of separation and divorce. Millions of families stayed at home for weeks due to the COVID-19 pandemic. For many parents of school-aged children, this meant homeschooling their children while also working from home, with everyone sharing resources (e.g. desk space, Internet bandwidth). For others, it meant facing unemployment and/or reduced income while spending far more time than usual with their partner or spouse. Among heterosexual couples, inequality in gender roles within the household could also be magnified in a context where they are spending more time together: conflicts over the distribution of paid and unpaid work could thereby arise, particularly for those homeschooling children while continuing paid work from home.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.214
GPT teacher head0.418
Teacher spread0.204 · 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
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

Citations0
Published2020
Admission routes1
Has abstractyes

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