Evolving Predictions for Executive Pay Features in Board Networks

Numerous recent studies in finance literature have shown that board networks are an important inter-corporate setting, influencing corporate decisions made by the board of directors, for example the determination of executive pay features. In this paper, we evolve predictors for the existence and adoption of several important pay features among S&P1500 companies, over the period 2006--2012. We use data from five well-known financial databases, including hundreds of variables containing both director-level and firm-level data. We present two approaches for predicting executive pay features. The first approach is based on a Genetic Algorithm (GA) used to evolve predictors based on weighted vectors of the predicting variables, providing relatively easy to understand prediction rules. The second approach employs Genetic Programming (GP) with sets of functions and terminals we devised specifically for this domain, based on contemporary research in finance. Thus, the GP approach explores a wider problem space and allows for more complex feature combinations. Experiments using both methods attain high quality prediction results, when compared to previous results in finance research. Additionally, our model is capable of successfully predicting combinations of pay features, compared to standard empirical models in finance, under various experimental conditions

How Reliable Are Assessments of Clinical Teaching?: A Review of the Published Instruments

BACKGROUND: Learner feedback is the primary method for evaluating clinical faculty, despite few existing standards for measuring learner assessments. OBJECTIVE: To review the published literature on instruments for evaluating clinical teachers and to summarize themes that will aid in developing universally appealing tools. DESIGN: Searching 5 electronic databases revealed over 330 articles. Excluded were reviews, editorials, and qualitative studies. Twenty-one articles describing instruments designed for evaluating clinical faculty by learners were found. Three investigators studied these papers and tabulated characteristics of the learning environments and validation methods. Salient themes among the evaluation studies were determined. MAIN RESULTS: Many studies combined evaluations from both outpatient and inpatient settings and some authors combined evaluations from different learner levels. Wide ranges in numbers of teachers, evaluators, evaluations, and scale items were observed. The most frequently encountered statistical methods were factor analysis and determining internal consistency reliability with Cronbach's α. Less common methods were the use of test-retest reliability, interrater reliability, and convergent validity between validated instruments. Fourteen domains of teaching were identified and the most frequently studied domains were interpersonal and clinical-teaching skills. CONCLUSIONS: Characteristics of teacher evaluations vary between educational settings and between different learner levels, indicating that future studies should utilize more narrowly defined study populations. A variety of validation methods including temporal stability, interrater reliability, and convergent validity should be considered. Finally, existing data support the validation of instruments comprised solely of interpersonal and clinical-teaching domains