Mapping the Landscape of Equitable Access to Advanced Neurotechnologies 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
ABSTRACT: Geographic, social, political, and economic factors shape access to advanced neurotechnologies, yet little previous research has explored the barriers, enablers, and areas of opportunity for equitable and meaningful access for diverse patient communities across Canada. We applied a mixed-mode approach involving semi-structured interviews and rating scale questions to consult with 24 medical experts who are involved in the care of patients who undergo functional neurosurgery targeting the brain. Seven major themes emerged from the qualitative analysis: Health care system , Neurotechnology features , Patient demographics , Target condition features , Ethics , Upstream barriers and enablers , and Areas of opportunity . Descriptive statistics of the Likert-scale responses suggest that interviewees perceive a disparity between the imperative of access to advanced neurotechnologies for people living in rural and remote areas and the likelihood of achieving such access. The results depict a complex picture of access to functional neurosurgery in Canada with pockets of excellence and a motivation to improve the availability of care for vulnerable populations through the expansion of distributed care models, improved health care system efficiencies, increasing funding and support for patient travel, and increasing awareness about and advocacy for advanced neurotechnologies.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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