Demographic Predictors of Attitudes Toward Capital Punishment: A Critical Multiple Regression Analysis

The question of attitudes to capital punishment has continued to be central to the criminal justice policy and mass opinion research. The research paper explores the stability and predictability of three demographic variables, which are core variables age, gender, and education, on the support of the death penalty. The analysis of interest was based on a predictive model using multiple regression analysis on secondary data of two independent samples (N 1 = 132 and N 2 = 150). Those findings showed that there was a significant paradox in the first sample, the overall model showed statistical significance (F(3,128)=9.209, *p=.001, R 2=.178), and age (404) and gender (0.404) turned out to be significant predictors, and education did not. The same model used on the second sample was, on the other hand, non-significant (F(3,146) =1.010, 3.90, R 2=0.20) and none of the predictors had any statistical significance. Such an extreme discrepancy evidences that the correlation between these fundamental demographics and attitudes towards the death penalty is not strong and constant in all situations. It is hypothesized in the interpretive conclusion that the divergence is probably because of sample-specific differences in compositional changes and that simplistic demographic models are subject to certain constraints. Such results are critical to the dependence of independent demographic variables and emphasize the need to develop more sophisticated and combined theoretical models that include psychosocial and contextual mediators, which are effective in explaining punitive attitudes.

Capital, Punishment, Criminal Justice. Multivariate Analysis, Demographics

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