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Child Development, Major Disruptive Events—Public Health Implications

2022· reference-entry· en· W4291291818 on OpenAlexaff
Tracy Vaillancourt, Péter Szatmári

Bibliographic record

VenueOxford Research Encyclopedia of Global Public Health · 2022
Typereference-entry
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsSafeguardingMental healthPandemicPositive Youth DevelopmentPsychologyPolitical sciencePublic healthCoronavirus disease 2019 (COVID-19)Economic growthPsychiatryCriminologyMedicineDevelopmental psychologyNursingDisease

Abstract

fetched live from OpenAlex

Abstract The COVID-19 pandemic has upended nearly all the safeguarding systems in the lives of children and youth, such as family life, school, extracurricular activities, sports, unstructured social opportunities, health care, and church. With many of the typical promotive and protective factors disrupted all at once, and for so long, the mental health of children and youth has deteriorated in many areas, but not all, and for many children and youth, but not all. It is important to acknowledge, however, that the mental health of children and youth was in crisis before the pandemic, with 1 in 7 children and youth worldwide having a mental disorder. Given the continued decline in this area of health, children and youth may well be on the cusp of a “generational catastrophe” that could involve lasting harms if immediate action is not taken. Of particular concern are marginalized and vulnerable children and youth—they are the ones unduly enduring the brunt of this global crisis. Accordingly, child and youth mental health recovery must be prioritized, along with the reduction of inequity within and across countries. A commitment to public health strategies that never include harming children and youth as a tolerated side effect must also be made.

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)0.021
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, 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: Review · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.006
Science and technology studies0.0110.001
Scholarly communication0.0000.001
Open science0.0030.004
Research integrity0.0010.011
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 head0.162
GPT teacher head0.473
Teacher spread0.311 · 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
GenreReview

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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