Struggling adolescent and young adult readers from the Ontario child welfare system
Bibliographic record
Abstract
Study 1 also used a reading classification system to categorize the 55 youth into one of three poor reader subtypes based on their pattern of cognitive deficit. Using criteria derived from the Double Deficit Hypothesis, 96% of the sample could be classified; 41% presented with a PA Deficit Only; 2% a RAN Deficit Only; and 57% a Double Deficit (DD). The DD subgroup were the most impaired readers. These results were compared to a school-aged sample of poor readers classified in Lovett, Steinbach and Frijters's (2000) study. This thesis describes the results from two studies. Study 1 examined the cognitive processing skills of 55 struggling readers from the child welfare system to determine whether their cognitive skills differed from the skills of struggling readers within the general population. The results showed these 55 youth presented with a pattern of cognitive deficits similar to that which characterizes poor readers in the general population. They showed deficits in phonological awareness (PA), rapid automatized naming (RAN), vocabulary, and memory. The cognitive skills of these 55 youth were also compared to the skills of 15 good readers from the child welfare system. Overall, the good readers performed significantly better than the poor readers on most of the cognitive measures although, individually, many of the good readers presented with weaknesses on these measures as well. In a second set of analyses, the good readers were matched onintelligence and age to a smaller sample of 15 poor readers. The results of these analyses were similar to the first set. In Study 2, 24 youth-in-care with poor reading skills participated in one of two reading programs (Program A or Program B) to see if either intervention would improve their reading. The results showed that participants made significant gains on the majority of measures administered to them at post-test. The youth in both programs made significant gains with Program A participants showing greater gains on only one of the measures, suggesting that the youth benefited equally from the programs. Youth with different patterns of cognitive deficit, based on the Double Deficit classification, also benefited equally from the two programs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".