Pediatric acquired brain injury resources for educators: a multi-year scan of Canadian-relevant internet resources
Bibliographic record
Abstract
BACKGROUND: Acquired Brain Injury (ABI) is the leading cause of death and disability in children, yet educators report a lack of knowledge about ABI and supporting students with ABI. With no formal learning about ABI, education professionals may turn to the internet for information. OBJECTIVES: To find online resources about supporting students with ABI, in any format, available freely and publicly, aimed toward elementary educators and that could be applied in a Canadian context. METHODS: We performed an environmental scan using keyword Google searches, key websites, and expert recommendations. The search was performed twice: 2018 and 2021. RESULTS: 96 resources were included after screening. The resources were published by organizations in the United States (n = 57), Canada (n = 19), United Kingdom (n = 16), Australia (n = 3) and New Zealand (n = 1). Traumatic brain injury and concussion were the most commonly addressed type of ABI, and Short Fact/Information sheets were the most common resource format. Between 2018 and 2021, 13 previously included resource links were no longer accessible. CONCLUSIONS: This scan suggests that there are many online resources available to educators in a variety of formats, and that information online can be transient. Future studies should evaluate the accuracy and quality of the resources available.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".