Melissa Kowalski
Biographic Data
| ID | 6031173 |
|---|---|
| NAME | Melissa Kowalski |
| GIVEN NAMES | Melissa |
| FAMILY NAME | Kowalski |
| SIGNATURE | KOWALSKI M |
| AFFILIATIONS | SUNY, Brockport, New York, USA |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Comparing Meters to Yards
Risk-needs assessments (RNAs) assist correctional staff in assigning supervision and programming. While gender is a well-known predictor of crime, for decades contemporary RNAs have claimed “gender-neutrality” or risk prediction equality for males and females. Unfortunately, females are frequently overclassified, relegated to a category higher than their risks indicate. Using ridge and mixed effects regression methods, we sought to enhance the pr…
Prediction is Local
In most states and jurisdictions, risk assessments are incorporated into justice system practice. Despite decades of use, the methods of tool development are rarely translated to the field. Many agencies implement ‘off-the-shelf’ versions, where a tool developed with a unique set of methods and subjects demonstrates prediction shrinkage when applied to a new jurisdiction. Using a large, 10-state sample of assessed youth (N=494,050), we isolate, t…
The great methods bake-off
No prominent works on this page.
Prediction is Local
In most states and jurisdictions, risk assessments are incorporated into justice system practice. Despite decades of use, the methods of tool development are rarely translated to the field. Many agencies implement ‘off-the-shelf’ versions, where a tool developed with a unique set of methods and subjects demonstrates prediction shrinkage when applied to a new jurisdiction. Using a large, 10-state sample of assessed youth (N=494,050), we isolate, t…
The great methods bake-off
Comparing Meters to Yards
Risk-needs assessments (RNAs) assist correctional staff in assigning supervision and programming. While gender is a well-known predictor of crime, for decades contemporary RNAs have claimed “gender-neutrality” or risk prediction equality for males and females. Unfortunately, females are frequently overclassified, relegated to a category higher than their risks indicate. Using ridge and mixed effects regression methods, we sought to enhance the pr…
Crime Patterns and Interventions (3 works) · Computer Science (2 works) · Criminal Justice and Corrections Analysis (2 works) · Law (2 works) · Machine learning (2 works) · Political science (2 works) · Psychopathy, Forensic Psychiatry, Sexual Offending (2 works) · Weighting (2 works) · Actuarial science (1 work) · Adversarial Robustness in Machine Learning (1 work)