Individual Differences in Speech and Language Ability Profiles in Areas of High Deprivation
Bibliographic record
Abstract
Speech and language ability is not a unitary concept; rather, it is made up of multiple abilities such as grammar, articulation and vocabulary. Young children from socio-economically deprived areas are more likely to experience language difficulties than those living in more affluent areas. However, less is known about individual differences in language difficulties amongst young children from socio-economically deprived backgrounds. The present research examined 172 four-year-old children from socio-economically deprived areas on standardised measures of core language, receptive vocabulary, articulation, information conveyed and grammar. Of the total sample, 26% had difficulty in at least one area of language. While most children with speech and language difficulty had generally low performance in all areas, around one in 10 displayed more uneven language abilities. For example, some children had generally good speech and language ability, but had specific difficulty with grammar. In such cases their difficulty is masked somewhat by good overall performance on language tests but they could still benefit from intervention in a specific area. The analysis also identified a number of typically achieving children who were identified as having borderline speech and language difficulty and should be closely monitored.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".