Building Inclusion Capacity in Early Childcare Settings: Replication of the Pyramid Model in Alberta
Bibliographic record
Abstract
This thesis examines a community-based replication of the Pyramid Model (PM) for promoting young children’s social–emotional competence in Alberta’s early learning and childcare (ELCC) sector through the Access, Support, and Participation (ASaP) initiative. Addressing the limited Canadian evidence base, the study evaluates implementation fidelity at both ELCC educator and program levels and explores how practice-based coaching (PBC) and leadership supports relate to change over time. A quantitative, longitudinal design was used. Fidelity data were collected between March 2022 and March 2024 using the Teaching Pyramid Observation Tool (TPOT; educator practice), Program-Wide Implementation Benchmarks of Quality (PWI-BoQ; program supports), and structured coaching logs. The analytic sample included 11 centres with complete multi-wave fidelity data and coaching records. Analyses included descriptive statistics, repeated-measures ANOVA, and correlations linking coaching exposure, program fidelity, and classroom practice. ELCC programs participated in ASaP for an average of 21 months. Educator fidelity rose from 40% at baseline to 74% at the fourth observation, with significant linear gains across most domains. PM program implementation supports increased from 28% to 72% across three waves. Time in ASaP correlated positively with stronger educator practices at mid- and late implementation (r = .741 at Time 2; r = .801 at Time 4). Greater leadership consultation was linked to higher TPOT scores at Time 4 (r = .544). The relationship between program implementation supports and educator practices strengthened over time, reaching significance at Time 3 (r = .773) and Time 4 (r = .900). With four educators achieving high-fidelity PM practices and five ELCC programs reaching program-wide implementation fidelity (80% across domains), this study offers preliminary evidence of the strength of the ASaP program in their delivery of the PM framework in a Canadian context. Findings suggest that ASaP’s blended supports—including professional learning, sustained coaching, and leadership consultation—are linked to meaningful, time-ordered improvements in PM fidelity within Canadian ELCC settings. Practically, systems may benefit from planning for 18–24 months of support and maintaining stability in coaching, leadership, and program monitoring data routines. Limitations include the small sample and absence of a comparison group. Future research should employ comparative designs, link fidelity to child outcomes, assess sustainment, and examine cost-effectiveness for provincial scaling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".