Bibliographic record
Abstract
This chapter presents an overview of J.P. Das’s influential research career, highlighting his early dissertation work on hypnosis and reactive inhibition, and his collaboration with Neil O’Connor in the area of developmental disabilities. In India, he broadened his research focus to include verbal conditioning and the impacts of adverse environments on cognitive skills, particularly among disadvantaged children. At the University of Alberta, his investigations centred on the attentional processes in individuals with mental retardation. Notably, Das’s 1973 study revealed how cultural deprivation affects cognitive processes in children from various backgrounds, establishing a link between nutrition, environment, and cognitive performance. His development of the PASS theory of intelligence provided a framework for understanding cognitive processing, leading to the creation of standardized assessments such as the DN-CAS and CAS2. Later, he concentrated on interventions to improve cognitive abilities and academic performance in learning disabled and culturally disadvantaged children, notably through programmes like the PASS Reading Enhancement Programme (PREP) and Cognition Enhancement Training (COGENT). These initiatives aimed to enhance cognitive and literacy skills, demonstrating significant impacts across clinical and educational contexts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.015 |
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".