Analysis Paper

ANALYSIS PAPER 3 INSTRUCTIONS Evaluating Gendered Patterns of Police Misconduct Using Cubitt et al. (2022) Total: 20 points (Graded entirely with the rubric) You will read the assigned Cubitt et al. (2022) article on Canvas very thoroughly and respond to each section below exactly as instructed. This is not a traditional essay. Submission and Formatting Requirements Submit your assignment as a Microsoft Word document (.doc or .docx) Include your full name at the top of the document Use Times New Roman, 12-point font Double-space the entire document Use headings exactly as they appear below Provide answers under each section, not in paragraph essay form Do not combine sections or omit headings Failure to follow formatting or submission instructions may result in point deductions. PART 1. Annotated Summary Provide answers under each heading in clear, complete sentences. APA Citation Write the full, correct APA 7 citation for the article. Research Question and Purpose Explain what the authors aimed to learn about: The extent to which serious misconduct differs between male and female officers Whether machine learning tools can classify officers by sex and predict serious misconduct Why examining gender in misconduct patterns and prediction models matters for policy and theory Data and Methods Describe the studys analytic approach, including: Use of the NYPD Civilian Complaint Review Board dataset Number of allegations, number of officers, and years covered Key variables (sex, age, rank, complaint types, serious misconduct indicator) Machine learning procedures (random forest models, logistic regressions, ROC curves) Use of propensity score matching to create comparable samples of male and female officers Use of partial dependence plots to interpret important predictors Sample Size, Time Frame, and Matching Design List and briefly describe: Number of officers in the dataset and number included after data cleaning Number of female officers and matched male officers Years of data used Why matching on age and rank matters for fair comparison How balance was assessed (standardized mean differences and variance ratios) Main Findings on Gender and Misconduct Summarize the major evidence-based results, including: Overall differences in serious misconduct rates between male and female officers Accuracy of machine learning models in predicting serious misconduct for each group Important predictors (prior serious misconduct, misuse of authority, age patterns, management action) How prediction strength differed between male and female officers Key patterns revealed by partial dependence plots PART 2. Analytical Evaluation Answer each section using explicit evidence and examples from the study. Is Misconduct Gender Neutral? Use evidence on prevalence rates, age patterns, complaint types, and prediction accuracy Assess whether male and female officers engage in misconduct in similar or different ways Machine Learning and Prediction of Serious Misconduct Discuss model performance and key predictors Explain what the results suggest about the potential benefits and risks of using advanced analytics for early intervention or risk identification Policy Implications of Gendered Misconduct Patterns Identify and explain at least two policy implications, such as: Limits of one-size-fits-all early intervention systems Importance of differentiating misconduct risk by officer characteristics Concerns about remedial actions failing to reduce future misconduct Insights for targeting repeat offenders and preventing high-cost incidents Each implication must be directly tied to empirical findings. Theoretical Contributions to Understanding Police Misconduct Connect the findings to: Gendered organization theory Social learning and strain explanations Opportunity structures and differential oversight Explain what this study adds to understanding why misconduct occurs and why gender matters. Strengths and Limitations of Administrative Complaint Data Discuss issues such as incomplete reporting, lack of internal complaint data, and equal weighting of all serious misconduct Explain benefits and challenges of transparency and public access to administrative data Ground your evaluation in the authors discussion of data constraints