Learning from failures of protocol in cross-cultural research.

The many tools that social and behavioral scientists use to gather data from their fellow humans have, in most cases, been honed on a rarefied subset of humanity: highly educated participants with unique capacities, experiences, motivations, and social expectations. Through this honing process, researchers have developed protocols that extract information from these participants with great efficiency. However, as researchers reach out to broader populations, it is unclear whether these highly refined protocols are robust to cultural differences in skills, motivations, and expected modes of social interaction. In this paper, we illustrate the kinds of mismatches that can arise when using these highly refined protocols with nontypical populations by describing our experience translating an apparently simple social discounting protocol to work in rural Bangladesh. Multiple rounds of piloting and revision revealed a number of tacit assumptions about how participants should perceive, understand, and respond to key elements of the protocol. These included facility with numbers, letters, abstract number lines, and 2D geometric shapes, and the treatment of decisions as a series of isolated events. Through on-the-ground observation and a collaborative refinement process, we developed a protocol that worked both in Bangladesh and among US college students. More systematic study of the process of adapting common protocols to new contexts will provide valuable information about the range of skills, motivations, and modes of interaction that participants bring to studies as we develop a more diverse and inclusive social and behavioral science.

Bridging Evolutionary Biology and Developmental Psychology: Toward An Enduring Theoretical Infrastructure.

Bjorklund synthesizes promising research directions in developmental psychology using an evolutionary framework. In general terms, we agree with Bjorklund: Evolutionary theory has the potential to serve as a metatheory for developmental psychology. However, as currently used in psychology, evolutionary theory is far from reaching this potential. In evolutionary biology, formal mathematical models are the norm. In developmental psychology, verbal models are the norm. In order to reach its potential, evolutionary developmental psychology needs to embrace formal modeling.

The costs and benefits of replication studies.

The debate about whether replication studies should become mainstream is essentially driven by disagreements about their costs and benefits and the best ways to allocate limited resources. Determining when replications are worthwhile requires quantifying their expected utility. We argue that a formalized framework for such evaluations can be useful for both individual decision-making and collective discussions about replication.

Competition for priority harms the reliability of science, but reforms can help.

Incentives for priority of discovery are hypothesized to harm scientific reliability. Here, we evaluate this hypothesis by developing an evolutionary agent-based model of a competitive scientific process. We find that rewarding priority of discovery causes populations to culturally evolve towards conducting research with smaller samples. This reduces research reliability and the information value of the average study. Increased start-up costs for setting up single studies and increased payoffs for secondary results (also known as scoop protection) attenuate the negative effects of competition. Furthermore, large rewards for negative results promote the evolution of smaller sample sizes. Our results confirm the logical coherence of scoop protection reforms at several journals. Our results also imply that reforms to increase scientific efficiency, such as rapid journal turnaround times, may produce collateral damage by incentivizing lower-quality research; in contrast, reforms that increase start-up costs, such as pre-registration and registered reports, may generate incentives for higher-quality research.

Why Hypothesis Testers Should Spend Less Time Testing Hypotheses.

For almost half a century, Paul Meehl educated psychologists about how the mindless use of null-hypothesis significance tests made research on theories in the social sciences basically uninterpretable. In response to the replication crisis, reforms in psychology have focused on formalizing procedures for testing hypotheses. These reforms were necessary and influential. However, as an unexpected consequence, psychological scientists have begun to realize that they may not be ready to test hypotheses. Forcing researchers to prematurely test hypotheses before they have established a sound "derivation chain" between test and theory is counterproductive. Instead, various nonconfirmatory research activities should be used to obtain the inputs necessary to make hypothesis tests informative. Before testing hypotheses, researchers should spend more time forming concepts, developing valid measures, establishing the causal relationships between concepts and the functional form of those relationships, and identifying boundary conditions and auxiliary assumptions. Providing these inputs should be recognized and incentivized as a crucial goal in itself. In this article, we discuss how shifting the focus to nonconfirmatory research can tie together many loose ends of psychology's reform movement and help us to develop strong, testable theories, as Paul Meehl urged.

Honest signaling in academic publishing.

Academic journals provide a key quality-control mechanism in science. Yet, information asymmetries and conflicts of interests incentivize scientists to deceive journals about the quality of their research. How can honesty be ensured, despite incentives for deception? Here, we address this question by applying the theory of honest signaling to the publication process. Our models demonstrate that several mechanisms can ensure honest journal submission, including differential benefits, differential costs, and costs to resubmitting rejected papers. Without submission costs, scientists benefit from submitting all papers to high-ranking journals, unless papers can only be submitted a limited number of times. Counterintuitively, our analysis implies that inefficiencies in academic publishing (e.g., arbitrary formatting requirements, long review times) can serve a function by disincentivizing scientists from submitting low-quality work to high-ranking journals. Our models provide simple, powerful tools for understanding how to promote honest paper submission in academic publishing.

Competition for novelty reduces information sampling in a research game-a registered report.

Incentive structures shape scientists' research practices. One incentive in particular, rewarding priority of publication, is hypothesized to harm scientific reliability by promoting rushed, low-quality research. Here, we develop a laboratory experiment to test whether competition affects information sampling and guessing accuracy in a game that mirrors aspects of scientific investigation. In our experiment, individuals gather data in order to guess true states of the world and face a tradeoff between guessing quickly and increasing accuracy by acquiring more information. To test whether competition affects accuracy, we compare a treatment in which individuals are rewarded for each correct guess to a treatment where individuals face the possibility of being 'scooped' by a competitor. In a second set of conditions, we make information acquisition contingent on solving arithmetic problems to test whether competition increases individual effort (i.e. arithmetic-problem solving speed). We find that competition causes individuals to make guesses using less information, thereby reducing their accuracy (H1a and H1b confirmed). We find no evidence that competition increases individual effort (H2, inconclusive evidence). Our experiment provides proof of concept that rewarding priority of publication can incentivize individuals to acquire less information, producing lower-quality research as a consequence.

Generalizability is not optional: insights from a cross-cultural study of social discounting.

Current scientific reforms focus more on solutions to the problem of reliability (e.g. direct replications) than generalizability. Here, we use a cross-cultural study of social discounting to illustrate the utility of a complementary focus on generalizability across diverse human populations. Social discounting is the tendency to sacrifice more for socially close individuals-a phenomenon replicated across countries and laboratories. Yet, when adapting a typical protocol to low-literacy, resource-scarce settings in Bangladesh and Indonesia, we find no independent effect of social distance on generosity, despite still documenting this effect among US participants. Several reliability and validity checks suggest that methodological issues alone cannot explain this finding. These results illustrate why we must complement replication efforts with investment in strong checks on generalizability. By failing to do so, we risk developing theories of human nature that reliably explain behaviour among only a thin slice of humanity.

DO SYMPTOMS OF ILLNESS SERVE SIGNALING FUNCTIONS? (HINT: YES).

Symptoms of illness provide information about an organism's underlying state. This notion has inspired a burgeoning body of research on organisms' adaptations for detecting and changing behavior toward ill individuals. However, little attention has been paid to a likely outcome of these dynamics. Once an organism's fitness is affected by others' responses to symptoms of illness, natural selection can favor individuals who alter symptom expression to influence the behavior of others. That is, many symptoms may originate as cues, but will evolve into signals. In this paper, I develop the hypothesis that symptoms of illness serve signaling functions, and provide a comprehensive review of relevant evidence from diverse disciplines. I also develop novel empirical predictions generated by this hypothesis and discuss its implications for public health. Signaling provides an ultimate explanation for otherwise opaque aspects of symptom expression, such as why symptoms fluctuate in social contexts, and can exist without underlying pathology, and why individuals deliberately generate symptoms of illness. This analysis suggests that signaling theory is a major organizing framework for understanding symptom etiology.