The Development of Bilingual Children’s Narrative Skills: A Report of the “Looking Glass Neighborhood” Program
Bibliographic record
Abstract
Abstract This paper evaluates Look Glass Neighborhood (LGN), an educational after-school program being experimented in San Diego, California. Following the theories of Vygotskian psychology and the “Fifth-Dimension” education model, LGN aims at improving bilingual children’s literacy via interactive games and letter writing activities. Based on previous studies on first language acquisition over past decades, the paper first discusses the inadequacy of research on child narrative development, especially in terms of the lack of attention to bilingual children and the insufficient discussion on applying first language acquisition theories to early literacy education. Then, it demonstrates the unique designs of the “Looking Glass Neighborhood” program by a qualitative analysis of ethnographic data from two elementary school bilingual participants in the program, explicating the program’s focuses on the interactions between oral performance and content-focused co-writing activities. Finally, the paper explores the possibility to embed some design elements of LGN such as content-based, co-writing activities and indirect oral corrective feedback into China’s current kindergarten and elementary EFL curriculums.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".