Are background variables good predictors of need for L2 assistance in school? Effects of age, L1, amount, and timing of exposure on Icelandic language and nonword repetition scores
Bibliographic record
Abstract
In response to the recent sharp increase of L2 students in Reykjavik schools, allocation criteria for special L2 services were adopted that were based on length of residence and on whether children’s home language was tonal or not tonal. This study set out to evaluate the appropriateness of these criteria, and to replicate previous findings of a smaller scale study of the Icelandic and nonword repetition performance of L2 learners of Icelandic.Participants: Included L2 learners and native speakers of Icelandic (n = 266) at three grade levels (grades 1–3, 5–6 and 8–9 (n = 266); the L2 learners included children from tonal and non tonal home languages.Method: All the children were administered a new test of Icelandic vocabulary and grammar developed expressly for Icelandic, a test of Icelandic nonword repetition, and a background information questionnaire.Results: L2 speakers in each age group performed significantly lower than L1 speakers in Icelandic vocabulary and grammar; less than a third of the L2 speakers performed within the normal L1 range, and over half performed more than 2 SD below this range. Low performers were particularly numerous in the oldest age group. NWR performance was related to age and Icelandic exposure, but scores were nevertheless uniformly high. No differences were found between children from tonal and non tonal home languages. The relationship between input and performance was complex, making fair allocation criteria based on background variables hard to formulate. Input variables (amount and timing of Icelandic exposure) were strongly related to input for the L2 group as a whole, and for the two older groups. However, the relationship was not significant for the youngest group. The pattern suggested that fast progress in Icelandic is related to higher age and recency of onset of L2 exposure.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".