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Record W3112779867 · doi:10.4103/wsp.wsp_45_20

Mental Health and Healthcare in Canada during the COVID-19 Epidemic: A Social Perspective

2020· article· en· W3112779867 on OpenAlexaffabout
KSonu Gaind

Bibliographic record

VenueWorld Social Psychiatry · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsHumber River Regional HospitalCanadian Mental Health AssociationUniversity of Toronto
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Perspective (graphical)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mental healthHealth carePandemicSociologyPsychologyMedicineVirologyPolitical sciencePsychiatryComputer scienceOutbreakDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The impacts of COVID-19, both through its direct infectious sequelae, and through massive changes to our societal and health system functioning, are being felt differentially by different populations. In many ways, the disproportionate negative impacts are highlighting preexisting fault lines in our social fabric. Lessons learned during this epidemic can hopefully help guide long-term improvements to models of health-care delivery, and also draw attention to needed social changes for addressing vulnerable marginalized populations and inequities, and improving social resilience.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.537
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.418
Teacher spread0.352 · 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 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

Citations10
Published2020
Admission routes2
Has abstractyes

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