Funding Priorities: Autism and the Need for a More Balanced Research Agenda in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The public purse is responsible for funding almost all autism spectrum disorders (ASD) research in Canada (as per Canadian Institutes of Health Research [CIHR]) and for providing some of the existing services and supports for this population. In this article, we consider various reasons why Canada should be concerned to ensure a more equitable distribution of relevant public funding for ASD research than is currently the case to meet the express needs and interests of the diversity of autism stakeholders. As such, we report data to show that CIHR-supported ASD research from the period of 2000–2010 demonstrates a bias focussed on the aetiology of the condition revealing a disproportionate emphasis on only two (Biomedical and Clinical) out of the four research pillars avowed by CIHR, with a comparative lack of fiscal resources committed to Health Systems and Services and Population and Public Health research. We advance certain normative and prudential reasons for funding more Health Systems and Services and Population and Public Health ASD research in Canada. In our view, this would seem to follow from CIHR’s official mandate ‘as a flexible mechanism that will continually align health research funding with changes in the manner in which health problems and opportunities are identified, understood and addressed’.
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.
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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it