Bibliographic record
Abstract
The main goal of this study is to review the role of the age factor in foreign language education and to discuss its implications in Korean English education. The younger, the better', under the critical period hypothesis, has recently played a critical role in the introduction of English language education to young children in Korea and the public and the government seem to be highly dependent upon the hypothesis when they decide childrens English education. For example, the English education program in Korean elementary schools is an offspring of this theory. This study, however, casts a doubt on the effect of age on English education by reviewing theoretical and experimental studies focusing on whether age or the critical period hypothesis is a meaningful factor to validate the early exposure of foreign language education and its following success. Findings from foreign language education in US, French immersion programs in Canada and other foreign countries and adult second language learning and studies dealing with the critical period hypothesis were critically reviewed to provide evidences to such argument that age is not a primary factor to determine early English education in Korea. On the contrary, time or the amount of exposure to the English language should be a more critical factor in a context where a very limited exposure to the target language is only possible. A list of generalizations and implications are also provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".