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Record W2999325794 · doi:10.29173/cjfy29492

GSS 2011 Linked with TIFF: Exploring the Cost of Child Care in Canada and the Use of the Child Care Tax Benefit

2019· article· en· W2999325794 on OpenAlexvenueaboutno aff
Leanne Findlay, Dafna Kohen

Bibliographic record

VenueCanadian Journal of Family and Youth / Le Journal Canadien de Famille et de la Jeunesse · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsChild careIndigenousFamily medicineDescriptive statisticsMedicinePsychologyBusiness

Abstract

fetched live from OpenAlex

Affordability of child care is fundamental to parents’, in particular, women’s decision to work. However, information on the cost of care in Canada is limited. The purpose of the current study was to examine the feasibility of using linked survey and administrative data to compare and contrast parent-reported child care costs based on two different sources of data. The linked file brings together data from the 2011 General Social Survey (GSS) and the annual tax files (TIFF) for the corresponding year (2010). Descriptive analyses were conducted to examine the socio-demographic and employment characteristics of respondents who reported using child care, and child care costs were compared. In 2011, parents who reported currently paying for child care (GSS) spent almost $6700 per year ($7,500 for children age 5 and under). According to the tax files, individuals claimed just over $3900 per year ($4,700). Approximately one in four individuals who reported child care costs on the GSS did not report any amount on their tax file; about four in ten who claimed child care on the tax file did not report any cost on the survey. Multivariate analyses suggested that individuals with a lower education, lower income, with Indigenous identity, and who were self-employed were less likely to make a tax claim despite reporting child care expenses on the GSS. Further examination of child care costs by province and by type of care are necessary, as is research to determine the most accurate way to measure and report child care costs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.250
Teacher spread0.212 · 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.

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
Published2019
Admission routes2
Has abstractyes

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