Additional Thoughts on Rigor in Wildlife Science: Unappreciated Impediments

Traditionally, most scientists accepted reductionist and mechanistic approaches as the rigorous way to do science. Sells et al. (2018) recently raised the argument about reliability in wildlife science. Chamberlin (1890), Platt (1964), Romesburg (1981, 1991, 2009), and Williams (1997) were rightly referenced as very influential papers. My intention in this letter is not to refute the essence of the Sells et al. (2018) commentary but to add seldom addressed but important aspects that influence the attainment of rigor and certainty in wildlife studies. The elements of a rigorous approach (i.e., strong inference) as described by Platt (1964) included devising alternative hypotheses, devising ≥1 crucial experiments that will exclude ≥1 of the hypotheses, and carrying out the experiment to get a clean result. The process was then repeated using logical inductive trees (i.e., a continually bifurcated statement hypotheses approach) to obtain the essential cause for the effect. Platt (1964) agreed with Popper (1959) that science advanced only by disproof. He argued that this was a hard doctrine and leads to disputations between scientists, but that Chamberlin\u27s (1890) method of multiple working hypotheses helped to remove that difficulty. Platt (1964) emphasized inductive inference and crucial and critical experiments whereby alternate hypotheses are refuted. Romesburg (1981) explained that in wildlife biology, induction (reliable associations) and retroduction (developing hypotheses) were the basis for almost all wildlife research but were not sufficient. He proposed the hypothetical‐deductive (H‐D) method as a more reliable approach. Citing Harvey (1969), and Popper (1962), Romesburg (1981:294) explained that “Starting with the research hypothesis, usually obtained by retroduction, predictions are made about other classes of facts that should be true if the research hypothesis is actually true.” The hypothesis is then tested indirectly by using logic to deduce one or more test consequences (Romesburg 2014). Data are then collected in a statistical framework. Romesburg (1981) distinguished between a research hypothesis (i.e., a conjecture about some process) versus a statistical hypothesis (i.e., a conjecture about classes of facts encompassed by the process). Williams (1997) clearly explained the differences between necessary and sufficient causation and gave examples of the coherent logic both entailed. He summarized that the science endeavor included theory, hypotheses, predictions, observations, and comparison of predictions against data, and argued that inductive and deductive logic were required for testing hypotheses. Importantly, Williams (1997:1014) recognized that wildlife biology often involves simultaneous complementary explanatory factors, requiring “the framing of many scientifically interesting issues about cause and effect in terms of the relative contribution of multiple causal factors.” Over the years, many others have addressed the issue of rigor and reliability in the Journal of Wildlife Management (JWM) and the Wildlife Society Bulletin (WSB) either directly (McNab 1983, Eberhardt 1988, Anderson 2001) or indirectly (Steidl et al. 1997, Guthery et al. 2001). This is not a complete list and is limited primarily to JWM and WSB but gives an idea of the wide interest in achieving reliable results from wildlife studies

Why Tenth Graders Fail to Finish High School: A Dropout Typology Latent Class Analysis

A large percentage of the students who drop out of K-12 schools in the United States do so at the end of high school, at some point after grade 10. Yet we know little about the differences between different types of students who drop out of the end of high school. The purpose of this study is to examine a typology of high school dropouts from a large nationally representative dataset (ELS:2002) using latent class analysis (LCA). We found three significantly different types of dropouts; Quiet, Jaded, and Involved. Based on this typology of three subgroups, we discuss implications for future dropout intervention research, policy, and practice

Leisure Behavior Pattern Stability During the Transition from Adolescence to Young Adulthood

Leisure is an important context in which human development occurs. Changes in leisure behavior patterns may indicate changing developmental needs or reflect contextual changes that impact leisure behavior. The transition from adolescence to young adulthood provides an excellent opportunity for the study of the stability of leisure behavior as individuals' contexts are changed with the adoption of adult roles and the potential for disruption of leisure patterns exists. Previous studies investigating leisure and the transition from adolescence to young adulthood have tended to be cross-sectional and focus on specific leisure behaviors rather than identifying patterns of leisure behavior. The present study involved a longitudinal investigation of leisure behavior patterns over a three-year period during the transition from adolescence to young adulthood, and determined the nature of leisure pattern stability and instability during this period. In general, leisure pattern stability was the most common pathway into young adulthood. The patterns of leisure behavior and the nature of the changes that occurred with the transition from adolescence to young adulthood differed to some degree for males and females, although similarities in patterns and transitions were also found.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45285/1/10964_2004_Article_411255.pd