Bibliographic record
Abstract
Mr. Killingsworth is nationally recognized for his pioneering efforts in cultivating the emerging domains of active living and placemaking – an applied science that considers the impact of the built environment on health. He has provided technical assistance to numerous federal agencies, national organizations, municipalities, and elected officials. He has consulted in over 300 communities; presented at over 100 national conferences; authored over 30 different peer reviewed publications; provided Congressional testimony; served on research and policy projects with the Centers for Disease Control, National Institutes of Health, National Academy of Sciences, and the World Health Organization; advised Health Canada and Transport Canada; and serves on several boards and national initiatives. Mr. Killingsworth has also conducted interviews with The Associated Press, USA Today, New York Times, Los Angeles Times, Washington Post, Chicago Tribune, Time, Outside Magazine, Jet, ABC News, NPR and PBS. Mr. Killingsworth is currently a Senior Advisor at Nemours Health and Prevention Services (NHPS) in Newark, Delaware. NHPS is a division of Nemours, an operating foundation that supports one of the nation's largest pediatric health care and health promotion systems. In this capacity, he oversees the strategic and operational integration of core business processes related to program development and implementation so NHPS can achieve its mission – to make Delaware’s children the healthiest in the nation.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".