Using a Policy of 'Gross National Happiness' to Guide the Development of Sustainable Early Learning Programs in the Kingdom of Bhutan: Aspirations and Challenges
Bibliographic record
Abstract
A national study on demand for early childhood care and development programs in Bhutan found strong support for development of a new early childhood care and development (ECCD) sector.┬a A wide range of stakeholders participating in the study, including ministries of education and health, post-secondary institutions, private preschool providers, community management committees, parents and children, emphasized the goal of preschool to promote success in English-medium formal education.┬a Promoting cultural traditions was also a priority, while developing childrenΓCOs proficiency in home languages was hardly mentioned. The study highlighted the changing needs of Bhutanese families in the current context of increasing urbanization, dual career parents, and a shift from extended to nuclear family homes. Recommendations derived from the study encouraged a made in Bhutan approach to ECCD policy, programs, and professional education.┬a Subsequent to the study, the national education policy included plans for implementation of ECCD covering children from birth to 8 years old. To ensure the sustainability and cultural congruence of new programs and investments with the KingdomΓCOs Gross National Happiness Policy, a Gross National Happiness Commission screened and approved the new National Education Policy, which the Ministry of Education is charged with implementing. The emergence of an ECCD sector in Bhutan points to the role that national aspirations and value-driven policies and review processes could play in maintaining language diversity and transmitting culturally based knowledge.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".