A Narrative Inquiry into Educational Decision-Making in Thai-Japanese Families in Thailand
Bibliographic record
Abstract
In the past decades, marriage migrants in Asia, including Thai-Japanese couples, have increased. Previous literature predominantly focused on issues related to adaptation and integration for foreign wives into the host society underlining the hypergamous (marrying a spouse of a higher status) nature of their marriage, which renders the majority of husbands and non-hypergamous marriages understudied. Therefore, the current study focuses on a population that includes husbands and wives, Japanese migrants, and Thai spouses. This study is exploratory and employed a qualitative approach with snowball sampling, which resulted in the inclusion of five Thai nationals and three of their Japanese spouses raising children in Thailand as participants. The study aims to examine their educational decision-making, including the language used in each family and school choice, since the parenting process is a succession of adjustments in response to the conditions of society, where values are explicitly manifested. Data were collected through face-to-face or online interviews, and content analysis was used to clarify themes. Analysis revealed factors that relate educational decisions to preconditions, such as the place of the first encounter, socioeconomic status, and location of their home. Another prominent issue is the strong belief in the English language. All participants claim that their decisions were made unanimously, while their characteristics, high levels of education and overseas experience, the preference of Japanese spouses to live in Thailand, and their lack of knowledge about educational options in Thai society contribute to the rational recount of their decision-making process.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".