Actividades musicales en escuelas infantiles de Hong Kong: Análisis de contenido de los informes de Revisión de Calidad
Bibliographic record
Abstract
In Hong Kong, the Education Bureau (EDB) assesses the quality of services provided to children in local kindergartens. Quality Review (QR) reports of kindergartens that pass the assessment are published on EDB’s website. We conducted a content analysis of 164 QR reports to examine the alignment between the music activities alluded to and the curriculum objectives established for music in official policies. A coding scheme was developed using both inductive and deductive approaches. High inter-reliability was obtained. MAXQDA was used to conduct word frequency, descriptive, and co-occurrence analyses. The most common terms identified in the music-related segments focused on children’s development of sensory abilities through music experiences, in relation to singing, rhythm, beat, movement, and instrumental music. However, activities intended to foster musical creativity and self-expression were seldom mentioned. We conclude that the QR reports reveal important discrepancies between official curriculum policies and actual classroom practices, which EDB assessors seemed to ignore or overlook. Implications focus on the need for kindergarten stakeholders to address curriculum/practice gaps and further prepare teachers to foster children’s musical creativity.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".