The article presents a meta-analysis of the relationship between job satisfaction and job performance, concluding that the true population correlation is relatively low (.17). Previous research variability is attributed to small sample sizes rather than unreliable measurement. Nine study design characteristics are only modestly related to the magnitude of the satisfaction-performance correlation. Despite negative conclusions from earlier reviews, research on this topic has continued, with a focus on causality, moderators, and methodological techniques. The meta-analysis approach, introduced by Glass (1976), allows for the integration of findings from multiple studies. Schmidt and Hunter's validity generalization method, an extension of meta-analysis, was also considered. The study used Hunter et al.'s (1982) method to integrate existing literature, finding that the true correlation between job satisfaction and performance is approximately .17, with a variance of .016. The results suggest that the magnitude of the satisfaction-performance correlation is not significantly influenced by the nine study characteristics examined. The study also found no significant differences in the magnitude of satisfaction-performance correlations over time. The analysis concluded that the true correlation is not significantly different from zero, but the variance in observed correlations is substantial. The study identified several potential sources of error variance, including range restriction, criterion contamination, and measurement differences. The results suggest that the relationship between job satisfaction and performance is weak and not strongly influenced by study characteristics. The study also found that some high correlations may be due to chance. The findings suggest that the relationship between job satisfaction and performance is not strong and that further research is needed to explore the factors that may influence this relationship.The article presents a meta-analysis of the relationship between job satisfaction and job performance, concluding that the true population correlation is relatively low (.17). Previous research variability is attributed to small sample sizes rather than unreliable measurement. Nine study design characteristics are only modestly related to the magnitude of the satisfaction-performance correlation. Despite negative conclusions from earlier reviews, research on this topic has continued, with a focus on causality, moderators, and methodological techniques. The meta-analysis approach, introduced by Glass (1976), allows for the integration of findings from multiple studies. Schmidt and Hunter's validity generalization method, an extension of meta-analysis, was also considered. The study used Hunter et al.'s (1982) method to integrate existing literature, finding that the true correlation between job satisfaction and performance is approximately .17, with a variance of .016. The results suggest that the magnitude of the satisfaction-performance correlation is not significantly influenced by the nine study characteristics examined. The study also found no significant differences in the magnitude of satisfaction-performance correlations over time. The analysis concluded that the true correlation is not significantly different from zero, but the variance in observed correlations is substantial. The study identified several potential sources of error variance, including range restriction, criterion contamination, and measurement differences. The results suggest that the relationship between job satisfaction and performance is weak and not strongly influenced by study characteristics. The study also found that some high correlations may be due to chance. The findings suggest that the relationship between job satisfaction and performance is not strong and that further research is needed to explore the factors that may influence this relationship.