Inclusive early childhood development (IECD): A twin-tracking approach to advancing behavioral health and social justice.
Bibliographic record
Abstract
As our American Orthopsychiatric Association (AOA) transforms into a Global Alliance for Behavioral Health and Social Justice (GABHSJ), early childhood development (ECD), and, particularly, inclusive early childhood development (IECD) persists as a prime pathway toward enhancing behavioral health and social justice. As we systematically and intentionally include consideration of the rights and needs of young children with disabilities and their families in our research, practice, and policy, a twin-track (TT) approach that simultaneously considers universal factors alongside disability-specific factors can enhance our conceptualization of problems and solutions. In the context of the sustainable development goals (SDGs) of the UN 2030 Agenda for Sustainable Development and its commitment to "leave no one behind," behavioral health and social justice enhancements derive from "mainstreaming" disability matters into diverse universal policies and programs. Elaborated in the triple-twin-track approach is a call for balancing child-centeredness, family focus, and community concerns as well as integrating the special and deepening knowledge of infants and young children with extant social policy and practice. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".