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Record W4256142848 · doi:10.32920/ryerson.14646804.v1

Voices From The Other Side: Perceptions Of Caregivers On Operating Unregulated Home-Based ChildCare

2021· preprint· en· W4256142848 on OpenAlexaff
Victoria Popov

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood DevelopmentHumber Polytechnic
Fundersnot available
KeywordsPoliticsPerceptionSnapshot (computer storage)Qualitative researchWork (physics)BusinessPublic relationsPolitical scienceSociologyPsychologySocial science

Abstract

fetched live from OpenAlex

The purpose of this qualitative study was to gain a snapshot of the unregulated home-based care sector (UHBC). All seven participants in this study were Caucasian females providing unregulated childcare on a full-time basis within their homes. Data collection took place in the form of semi-structured interviews. The UHBC providers’ perceptions about their work were examined through the theoretical lens of the political economy of care that encompasses features such as social reproduction, grey market economy, transnationalization of care, and solutions that address political economy of care. The analysis revealed that the unregulated services UHBC providers offer embody a political economy of care. However, in addressing a political economy of care, the UHBC providers believe that they are meeting families’ needs, and wish for a better regulation of UHBC. A possible system of UHBC regulation is proposed.

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)0.008
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.011
Scholarly communication0.0050.005
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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