Maggie Beverly
Biographic Data
| ID | 145755 |
|---|---|
| NAME | Maggie Beverly |
| GIVEN NAMES | Maggie |
| FAMILY NAME | Beverly |
| SIGNATURE | BEVERLY M |
| AFFILIATIONS | Drexel University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Research and Evaluation in a Child-Focused Place-Based Initiative: West Philly Promise Neighborhood
Place-based initiatives attempt to reduce persistent health inequities through multisectoral, cross-system collaborations incorporating multiple interventions targeted at varying levels from individuals to systems. Evaluations of these initiatives may be thought of as part of the community change process itself with a focus on real-time learning and accountability. We described the design, implementation, challenges, and initial results of an eva…
Improving Sampling Probability Definitions with Predictive Algorithms
Place-based initiatives often use resident surveys to inform and evaluate interventions. Sampling based on well-defined sampling frames is important but challenging for initiatives that target subpopulations. Databases that enumerate total population counts can produce overinclusive sampling frames, resulting in costly outreach to ineligible participants. Quantifying eligibility before sampling using machine learning algorithms can improve effici…
No prominent works on this page.
Research and Evaluation in a Child-Focused Place-Based Initiative: West Philly Promise Neighborhood
Place-based initiatives attempt to reduce persistent health inequities through multisectoral, cross-system collaborations incorporating multiple interventions targeted at varying levels from individuals to systems. Evaluations of these initiatives may be thought of as part of the community change process itself with a focus on real-time learning and accountability. We described the design, implementation, challenges, and initial results of an eva…
Improving Sampling Probability Definitions with Predictive Algorithms
Place-based initiatives often use resident surveys to inform and evaluate interventions. Sampling based on well-defined sampling frames is important but challenging for initiatives that target subpopulations. Databases that enumerate total population counts can produce overinclusive sampling frames, resulting in costly outreach to ineligible participants. Quantifying eligibility before sampling using machine learning algorithms can improve effici…
Computer Science (2 works) · Accountability (1 works) · Blueprint (1 works) · Business (1 works) · Child and Adolescent Health (1 works) · Community Health and Development (1 works) · Computer security (1 works) · Dashboard (1 works) · Data collection (1 works) · Data mining (1 works)