Raising a Child with Early Childhood Dis-ability Supports Shakonehya:ra's ne shakoyen'okon:'a G’chi-gshkewesiwad binoonhyag ᑲᒥᓂᑯᓯᒼ ᑭᑫᑕᓱᐧᐃᓇ ᐊᐧᐊᔕᔥ ᑲᒥᓂᑯᓯᒼ ᑲᐧᐃᔕᑭᑫᑕᑲ : Ga-Miinigoowozid Gikendaagoosowin Awaazigish, Ga-Miinigoowozid Ga-Izhichigetan
Bibliographic record
Abstract
The Inclusive Early Childhood Service System Project (IECSS) is a qualitative longitudinal study of families’ experiences of accessing services for their children who have disabilities or developmental delays in early childhood.This article presents findings and analysis of data from Indigenous participants in the IECSS study. The study found that Indigenous families were often very engaged in culturally specific services for their children and families, in addition to accessing mainstream disability support services. Further, the study found that the system operatesfrom a colonial framework that does not align with Indigenous ways of child-rearing and knowledge of human diversity. Consequently, the underlying ideological differences often lead to conflict for Indigenous families as they seek to maintain their cultural understandings of development while accessing supports for their children. These findings suggest that Indigenous concepts of disability and childhood need to be integrated into the current disability support system to increase access and efficacy.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".