Systematic review of the literature on characteristics of late‐talking toddlers
Bibliographic record
Abstract
BACKGROUND: Research has investigated late-talking toddlers because they are at great risk of continuing to experience language-learning difficulties once they enter school and hence are candidates for early intervention. It is also important to consider this group of children with regards to the immediate characteristics which are detrimental to their development and for which early intervention has become increasingly available. AIMS: To review the literature on late-talking toddlers in order to identify the characteristics of this population whose importance has been clearly demonstrated, identify sources of incongruence in findings, and to underscore aspects of language delay at 2 years of age and characteristics about which additional knowledge is needed. MAIN CONTRIBUTION: The review highlights the need to define the language difficulties found in late-talking toddlers based on clinical profiles that go beyond the criterion of an expressive vocabulary delay. It also underscores the association between vocabulary delay and characteristics of the child such as social-emotional development and characteristics of the socio-familial environment such as language stimulation. CONCLUSIONS: Future research should take into account the lack of homogeneity observed within the population of children with a vocabulary delay at 2 years of age and attempt to identify subgroups within late-talking toddlers. It should also consider a multifactorial perspective of child development to further the understanding of this phenomenon.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".