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Record W3111541156 · doi:10.3167/ghs.2020.130301

The Lives of Girls and Young Women in the Time of COVID-19

2020· article· en· W3111541156 on OpenAlexaff
Claudia Mitchell, Ann Smith

Bibliographic record

VenueGirlhood Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsMcGill University
Fundersnot available
KeywordsPandemicShadow (psychology)Social distanceCoronavirus disease 2019 (COVID-19)Isolation (microbiology)PatriarchyGender studiesPsychologySocial isolationCriminologySociologyPolitical scienceMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

As with Zika, Ebola, HIV and AIDS, and other pandemics in recent history, girls and young women are particularly vulnerable to COVID-19 socially and emotionally if not medically. Some observers have referred to the current crisis as a tale of two pandemics in reference to both the obvious health issues and the pervasive gender inequalities that have become exacerbated, and others have referred to it as “the shadow pandemic” (UN Women 2020: n.p.) in highlighting the negative impact that physical distancing and social isolation are having on already vulnerable girls and young women experiencing sex- and gender-based violence. All over the world girls and young women are facing increasing levels of precariousness as a direct result of the health measures being taken to curb the global transmission of COVID-19. The increasing lack of privacy in the home furthers the practice of cultural forms of patriarchy that lead to violence.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.005
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.078
GPT teacher head0.289
Teacher spread0.211 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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