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Record W1998905163 · doi:10.12927/hcq.2011.22573

Combining Vision with Evidence for Child Health and Well-Being Indicators in British Columbia

2011· article· en· W1998905163 on OpenAlexaffabout
Eric H. Young, Michael Egilson, Nancy Gault, Bernie Paillé

Bibliographic record

VenueHealthcare Quarterly · 2011
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsIsland Health
Fundersnot available
KeywordsPublic relationsTransparency (behavior)OfficerPopulationHealth indicatorSet (abstract data type)Population healthMedicinePsychologyPolitical scienceMedical educationEnvironmental healthLaw

Abstract

fetched live from OpenAlex

ow does a society know if the health and wellbeing of children and youth are improving, staying the same or getting worse?If one was to choose a manageable set of indicators to follow over a 20-year period, what would it look like?Since we know that what gets measured focuses attention, programming and funding, the question is this: what measures, covering which aspects of the lives of children and youth, should be selected from a population perspective?Given the variety of world views that exist among the many child and youth service providers, as well as the multiple definitions of health and well-being, this question is particularly difficult to answer.This is what the provincial health officer (PHO) of British Columbia is facing with an upcoming report that will look at the health and well-being of children and youth in the province.To answer these questions the Office of the PHO has partnered with the Canadian Institute for Health Information (CIHI) to identify a set of indicators to define and track child health and well-being in British Columbia.The process of identifying this suite of indicators is committed to transparency, evidence and collaboration.Over a decade ago, the PHO (1998) published a comprehensive report on the health of children in British Columbia, with more focused reports since then.At the time, the report was groundbreaking in that it looked at child health beyond physical health and considered how the social determinants of health impacted the lives of children.Building on this tradition, the PHO's vision for the updated report is that it will identify the factors and modifiable conditions and actions that truly make the most difference to both positive and negative child and youth health and well-being outcomes, and will inform health system decision-making in terms of policy, programs and services aimed at improving the lives of children in British Columbia.The PHO's goal is to have a sustainable, solid measurement system that will support consistent and ongoing reporting over many years. Project governanceThe project engages multiple government ministries and stakeholders involved in the delivery of services and programs.The structure of the project consists of three supporting bodies: About the AuthorsEric Young, mD, mhsc, ccfp, frcpc, is the deputy provincial health officer for british columbia, in Victoria, british columbia.Michael Egilson, ba, bsW, ma, is the project lead, child health indicator project, for the bc ministry of health. nancy gault,

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)0.020
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.070
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.016
Science and technology studies0.0020.001
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.002
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 head0.043
GPT teacher head0.371
Teacher spread0.328 · 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 designQualitative
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

Citations1
Published2011
Admission routes2
Has abstractyes

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