‘All parents want <i>caregivers to protect and love their children</i> ’: perceptions of childcare workers, trainers, and government officials in Vietnam
Bibliographic record
Abstract
Access to high-quality childcare can have multi-generational impacts, including improved employment opportunities for women and improved child outcomes. Despite an increasing number of women entering the workforce in low- and middle-income countries, the definition of ‘quality’ childcare stems largely from westernised, high-income, countries. This qualitative study aimed to understand how childcare quality is conceptualised by key stakeholders in informal childcare settings in the industrialised zones of Da Nang and Quang Nam Provinces in Vietnam. Twenty-nine stakeholders were interviewed including, childcare center trainers (n = 6), government stakeholders (n = 6), childcare center providers (n = 8), and parents (n = 9) through in-depth interviews conducted in December 2019 and June to July of 2020. We found that our stakeholders’ perspectives could be categorised into two themes, structural quality, including the learning environment and childcare-provider interactions, and process quality, including childcare-provider interactions and other aspects that promote early child development. Although our broad theme findings are consistent with the exiting literature, stakeholders emphasised context-specific markers of quality, such as children’s obedience and happiness, as essential outcomes of care. These insights provide a culturally grounded understanding of quality in Vietnam’s informal childcare sector, with implications for future policy and programming.Abbreviations: LMIC: low-and-middle-income country; ECCE: early childhood care and education; SDG: sustainable development goal; ECD: early childhood development; HBC: home-based care
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".