Services Delivered by Specialized Professionals in Childcare Settings in Québec, Canada: Strengths and Limitations of Current Service Delivery Models
Bibliographic record
Abstract
BACKGROUND: Specialized professionals, including healthcare professionals and early childhood special educators (ECSEs), wish to offer more in-context interventions in childcare settings. Limited information is available about how these services are and should be organized. The aim of this study was to describe the different service delivery models currently used in a context of publicly funded healthcare and childcare systems (Québec, Canada) and to identify the strengths and limitations of these models. METHODS: An interpretative descriptive research approach was used. Qualitative data from an online survey (n = 344) and semi-structured interviews (n = 18) were used. Questions focused on the description of services (e.g., type of specialized professionals involved, children served, funding) and strengths and limitations of those services. Data were coded using thematic analysis. RESULTS: Data were classified into 10 service delivery models and are presented using a four-quadrant paradigm based on the source of funding (either internal [childcare-led] or external to childcare) and the focus of service (either child-centred or childcare-centred). Services funded by childcare providers (Quadrants 1 and 3) offered flexibility in addressing priority needs identified by childcare providers and facilitated collaboration with early childhood educators. Childcare-centred models (Quadrants 3 and 4) addressed the needs of children not receiving individual healthcare services. Healthcare-funded services (Quadrants 2 and 4) provided free services for childcare providers. CONCLUSIONS: Each service delivery model had its own strengths and limitations. To enhance support for childcare providers and the children they serve, stakeholders should consider using a variety of service delivery models covering all four quadrants. Three key actions should be considered to improve current services: (1) incorporate more childcare-centred services to reduce the number of underserved children; (2) offer more childcare-led services to align with priority needs identified by childcare providers; and (3) improve intersectoral collaboration by developing cross-institutional policies. KEY MESSAGES: A variety of service delivery models is needed to enhance support for childcare providers and the children they serve. Childcare-centred service delivery models could serve a greater number of children, particularly those underserved by child-centred service delivery models. Childcare-led service delivery models are needed to align services with the needs and priorities identified by childcare providers. Healthcare and childcare systems would benefit from formalized cross-institutional policies to facilitate intersectoral collaboration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".