Reciprocal intercompatibility between Byrsonima Rich. exKunth species (Malpighiaceae), in an urban ecotonal fragment of Semi-Deciduous Seasonal Forest and Cerrado

Byrsonima species present floral monomorphism and sharing visitor/pollinator guild. These traits suggest the hypothesis evaluation of reciprocal inter-incompatibility between two syntopic Byrsonima species: B. pachyphylla and B. crassifolia. Pollen tube growth with similar behavior was observed in the stigmatic surface, pistil canal, ovary and micropylar channel to both species. In addition, partial self-incompatibility in self-pollination with greater fruiting in autogamy was observed. Cross-pollination and self-pollination coexist, and reciprocal intercompatibility occurs. Prezygotic isolation mechanisms are unlikely by the absence of abnormal pollen tubes, higher fruiting production and absence of hybrids in the study site. Las especies de Byrsonima presentan monomorfismo floral y comparten gremio de visitantes/polinizadores. Estos rasgos sugieren la evaluación de hipótesis de interincompatibilidad recíproca entre dos especies sintópicas de Byrsonima: B. pachyphylla y B. crassifolia. Se observó el crecimiento del tubo polínico con comportamiento similar en la superficie estigmática, canal del pistilo, ovario y canal micropilar de ambas especies. Además, se describió la autoincompatibilidad parcial en la autopolinización con mayor fructificación en la autogamia. La polinización cruzada y la autopolinización coexisten y se produce una intercompatibilidad recíproca. Los mecanismos de aislamiento precigóticos son improbables por la ausencia de tubos polínicos anormales, producción de frutos y ausencia de híbridos en la área de estudio.

Studying science denial with a complex problem-solving task

Explanations of science denial rooted in individual cognition tend to focus on general trait-like factors such as cognitive style, conspiracist ideation or delusional ideation. However, we argue that this focus typically glosses over the concrete, mechanistic elements of belief formation, such as hypothesis generation, data gathering, or hypothesis evaluation. We show, empirically, that such elements predict variance in science denial not accounted for by cognitive style, even after accounting for social factors such as political ideology. We conclude that a cognitive account of science denial would benefit from the study of complex (i.e., open-ended, multi-stage) problem solving that incorporates these mechanistic elements.

Teacher’s Reasons for Trust and Distrust in Scientific Evidence: Reflecting a “Smart But Evil” Stereotype?

We investigate in-service teachers’ reasons for trust and distrust in educational research compared to research in general. Building on previous research on a so-called “smart but evil” stereotype regarding educational researchers, three sets of confirmatory hypotheses were preregistered. First, we expected that teachers would emphasize expertise—as compared with benevolence and integrity—as a stronger reason for trust in educational researchers. Moreover, we expected that this pattern would not only apply to educational researchers, but that it would generalize to researchers in general. Furthermore, we hypothesized that the pattern could also be found in the general population. Following a pilot study aiming to establish the validity of our measures (German general population sample; N = 504), hypotheses were tested in an online study with N = 414 randomly sampled German in-service teachers. Using the Bayesian informative hypothesis evaluation framework, we found empirical support for five of our six preregistered hypotheses.

A Review of Applications of the Bayes Factor in Psychological Research

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The paper is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines.

Explanation Supports Hypothesis Generation in Learning

A large body of research has shown that engaging in explanation improves learning across a range of tasks. The act of explaining has been proposed to draw attention and cognitive resources toward evidence that will support a good explanation—information that is broad, abstract, and consistent with prior knowledge—which in turn aids discovery and generalization. However, it remains unclear whether explanation acts on the learning process via improved hypothesis generation, increasing the probability that the correct hypothesis is considered in the first place, or hypothesis evaluation, the appraisal of the correct hypothesis in light of evidence. In the present study, we address this question by separating the hypothesis generation and evaluation processes in a novel category learning task and quantifying the effect of explanation on each process independently. We find that explanation supports the generation of broad and abstract hypotheses but has less effect on the evaluation of hypotheses.

Cognitive Decision Process: The Context of Auditors' Diagnostic Reasoning

Based on a cognitive psychology framework, this article provides an insight into how auditors perform diagnostic reasoning tasks through an analytical review (AR) process. AR refers to the diagnostic process of identifying, investigating, and resolving unexpected fluctuations in account balances and other financial relationships in financial statements. Auditors perfuming AR typically follow four distinct components of a diagnostic, sequential and iterative (DS1) process, namely: mental representation, hypothesis generation, information search, and hypothesis evaluation. Through the DS1 process, auditors are able to recognize and detect errors and irregularities in financial statements for the purpose of presenting a true and fair view of financial reporting, with the intention of communicating quality and reliable economic information of an enterprise to users.

Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10,000 Robot Swarm

When designing swarm-robotic systems, system- atic comparison of algorithms from different do- mains is necessary to determine which is capa- ble of scaling up to handle the target problem size and target operating conditions. We propose a set of quantitative metrics for scalability, flexibility, and emergence which are capable of addressing these needs during the system design process. We demonstrate the applicability of our proposed met- rics as a design tool by solving a large object gath- ering problem in temporally varying operating con- ditions using iterative hypothesis evaluation. We provide experimental results obtained in simulation for swarms of over 10,000 robots.