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Record W3182401904 · doi:10.1177/0192513x211022386

Policy Frameworks and Parental Choice: Using Conjoint Analysis to Understand Parental Decision Making for Child Care

2021· article· en· W3182401904 on OpenAlexafffundabout
Adrienne Davidson, Samantha Burns, Delaine Hampton, Linda A. White, Michal Perlman

Bibliographic record

VenueJournal of Family Issues · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of TorontoMcMaster University
FundersHarrison McCain Foundation
KeywordsRubricChild careConjoint analysisPreferenceQuality (philosophy)Early childhood educationVariety (cybernetics)PsychologyEarly childhoodNursingDevelopmental psychologyMedicineEconomicsPedagogy

Abstract

fetched live from OpenAlex

Many children in Canada and the United States experience poor-quality child care on a regular basis. Under the rubric of “parent choice,” governments continue to permit a variety of licensed care providers (centers and homes) as well as unlicensed home child care providers. Research suggests, however, that parents are not well-informed consumers about child care services, unaware of even the basic characteristics of their child’s care. In this study, we provide findings from a latent profile analysis based on a conjoint survey conducted in Toronto, Canada to better understand the factors that influence parents’ decisions in selecting child care services. Based on responses from over 700 parents, we identify five classes of parents that reflect a range of preferences in selecting child care. However, most groups show a strong preference for licensed early childhood education and care (ECEC) options. Limitations of this study and implications for policy are discussed.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.061
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.425
Teacher spread0.380 · 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

Citations19
Published2021
Admission routes3
Has abstractyes

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