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Record W2910212442 · doi:10.25071/1705-1436.153

The Union Advantage in Child Care: How Unionization Can Help Recruitment and Retention

2004· article· en· W2910212442 on OpenAlexvenueaboutno aff
Jamie M. Kass, Bozica Costigliola

Bibliographic record

VenueJust Labour · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsChild careDemocracyQuality (philosophy)Service (business)BusinessPolitical sciencePublic relationsPsychologyLabour economicsNursingEconomicsMedicineMarketingLaw

Abstract

fetched live from OpenAlex

Unions exert a positive influence in child care workplaces and in the sector generally. Unionization is an important strategy for dealing with recruitment and retention, two of the biggest challenges facing the sector in Canada today. Overall, unionized child care workplaces contribute to higher quality programs and attract more experienced and more trained early childhood educators. Unions support a model of professionalism and workplace relationships that is inclusive, democratic and collective. They support professional development, affordable education and regulation of the service and the occupation. They are longstanding advocates for women’s equality, and a publicly funded child care system.

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)0.016
metaresearch head score (Gemma)0.026
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 score0.017
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0120.010
Scholarly communication0.0100.009
Open science0.0020.010
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0160.001

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 head0.056
GPT teacher head0.364
Teacher spread0.308 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

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