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Record W1494299206 · doi:10.1093/pch/12.8.661

Oh Canada! Too many children in poverty for too long

2007· article· en· W1494299206 on OpenAlexaboutno aff
Laurel Rothman

Bibliographic record

VenuePaediatrics & Child Health · 2007
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyEconomic growthGovernment (linguistics)Child povertyBasic needsAffordable housingExtreme povertyDevelopment economicsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Despite continued economic growth, Canada's record on child poverty is worse than it was in 1989, when the House of Commons unanimously resolved to end child poverty by the year 2000. Most recent data indicate that nearly 1.2 million children – almost one of every six children – live in low-income households. Campaign 2000 contends that poverty and income inequality are major barriers to the healthy development of children, the cohesion of our communities and, ultimately, to the social and economic well-being of Canada. Canada needs to adopt a poverty-reduction strategy that responds to the UNICEF challenge to establish credible targets and timetables to bring the child poverty rate well below 10%, as other Organisation for Economic Co-operation and Development nations have done. Campaign 2000 calls on the federal government to develop a cross-Canada poverty-reduction strategy in conjunction with the provinces, territories and First Nations, and in consultation with low-income people. This strategy needs to include good jobs at living wages that ensure that full-time work is a pathway out of poverty; an effective child benefit of $5,100 that is indexed; a system of affordable, universally accessible early learning and child care services available to all families irrespective of employment status; an affordable housing program that creates more affordable housing and helps to sustain existing stock; and affordable and accessible postsecondary education and training programs that prepare youth and adults for employment leading to economic independence. Malgré une croissance économique constante, la situation canadienne en matière de pauvreté des enfants est pire qu'en 1989, lorsque la Chambre des communes a résolu à l'unanimité de mettre un terme à la pauvreté avant l'an 2000. Selon les données les plus récentes, près de 1,2 million d'enfants, soit près de un enfant sur six, vivent dans un ménage à faible revenu. D'après Campagne 2000, la pauvreté et l'inégalité des revenus sont d'importants obstacles au sain développement des enfants, à la cohésion des collectivités et, en définitive, au bien-être social et économique du Canada. Le Canada doit adopter une stratégie de réduction de la pauvreté qui répond au défi lancé par l'UNICEF : fixer des objectifs et des échéanciers crédibles pour faire chuter le taux de pauvreté des enfants bien au-dessous des 10 %, à l'instar d'autres nations de l'Organisation de coopération et de développement économiques. Campagne 2000 demande au gouvernement fédéral de créer une stratégie pancanadienne de réduction de la pauvreté, conjointement avec les provinces, les territoires et les Premières nations et en consultation avec les ménages à faible revenu. Cette stratégie doit inclure de bons emplois à un salaire minimum vital suffisant pour garantir que le travail à temps plein permette de se sortir de la pauvreté, des allocations pour enfant de 5 100 $ qui sont indexées, un système de services d'apprentissage et de soins de la petite enfance abordables et universels à la disposition de toutes les familles, quel que soit leur statut d'emploi, un programme de logement abordable qui comporte plus d'habitations à loyer modique et contribue au maintien des avoirs ainsi qu'une éducation postsecondaire et des programmes de formation abordables et accessibles qui préparent les jeunes et les adultes à des emplois qui leur assureront une autonomie financière.

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: none
Teacher disagreement score0.279
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0130.003
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.2790.057

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 head0.055
GPT teacher head0.391
Teacher spread0.336 · 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

Citations20
Published2007
Admission routes1
Has abstractyes

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