Abstract 3024: School is Out : Creating Stroke Detectives through Summer Challenge
Bibliographic record
Abstract
Background: Childhood obesity and early-onset diabetes are on the rise. The American Heart Association Heart Disease and Stroke Statistics indicate that the unhealthy behaviors that are the risk factors for stroke begin with school-aged children. In 2009, our organization created a stroke awareness program for high schools and youth groups that demonstrated retention of knowledge in a pre-post test format. The content was developed to be relevant for that specific age group. Purpose: Building on that success and the need for earlier education, we developed a Stroke Detective Summer Challenge for elementary age children. Method: This independent, structured program was made available through the stroke center website. Packets were also placed at three local libraries and provided to 3 rd graders at a local summer day camp. The program content included the stroke detective pledge (written by the stroke program coordinator), an activity book, an exercise & healthy eating log, and a scavenger hunt. To qualify as a stroke detective, participants were required to: 1) sign the pledge; 2) share their stroke knowledge with 5 people by giving them a F.A.S.T. (face, arm, speech, time) card and getting their signatures; and 3) return the signature page along with their completed exercise & healthy eating log and their T-shirt size. Results: A summer’s end celebration for the 22 new “stroke detectives” included stations for making a healthy snack and for some simple physical activity competitions. They each received a detective bag, healthy snack recipes, giveaways, and a Stroke Detective T-shirt. These young detectives, along with their parents and siblings were greeted by our hospital mascot and were given a tour of our helicopter. The students, supported by their parents, enthusiastically described their pride in becoming stroke detectives. Conclusions: Our previous successful experience with making educational content relevant for specific age groups was repeated in this unique initiative. We demonstrated that stroke awareness education does NOT have to be complex or scary; in fact, by introducing simple facts at a young age, we may help eliminate the fear and ignorance that has made community awareness of stroke such a challenge in the past. They could become the first generation of adults to know that a stroke does not occur in the heart.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.013 |
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".