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Record W4388806526 · doi:10.5694/mja2.52144

Having material basics is basic

2023· article· en· W4388806526 on OpenAlexaboutno aff
Sharon Goldfeld, Anna Price, Fadwa Al‐Yaman

Bibliographic record

VenueThe Medical Journal of Australia · 2023
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersVicHealth
KeywordsPovertyHarmIndigenousPsychologyPublic relationsEconomic growthPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

PerspectiveHaving material basics is basic M aterial basics are essential for our health and wellbeing.1 They represent one of seven domains considered in this supplement on the Future Healthy Countdown 2030.The Nest framework, developed by the Australian Research Alliance for Children and Youth, defined this domain in 2021 through interviews with children and young people. 2 According to their collective voices, material basics include stable and suitable housing, nutritious food, and clean water and air. 2 They also include necessary school supplies and technology, the ability to take part in social activities, and access to transport and open spaces. 2 Material basics are met when families have enough money for all these needs and items.1,2 Children who are raised in families experiencing material deprivation -such as poverty, homelessness or social exclusion -have increased risks of psychological or socio-emotional difficulties, behavioural problems, educational difficulties, and poor mental health as they grow.3,4 Australia's children and young people shoulder specific inequities.The greatest gaps in outcomes and opportunities exist between Aboriginal and/or Torres Strait Islander families and non-Indigenous families.5 They are also common for children in rural and remote settings compared with those in major cities. 5 Not only a problem for the individual, these entrenched, lifelong disparities harm society by increasing health service costs and reducing economic productivity.6 Meeting basic material needs buffers children, young people and families from the negative consequences of early adversity and enhances the environments that support all children to thrive.7

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)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0050.006
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1240.033

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 head0.053
GPT teacher head0.346
Teacher spread0.292 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2023
Admission routes1
Has abstractyes

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