Michael R. Dougherty

Diverse factors, including environmental features and cognitive processes, can drive animals’ movements and space use, with far-reaching implications. For example, repeated use of individual-level travel routeways (directionally constrained but imperfectly aligned routes), which results in spatial concentration of activity, can shape encounter-based processes including predation, mate finding, and disease transmission. However, how much variation in routeway usage exists across species remains unknown. By analyzing GPS movement tracks for 1,239 range-resident mammalian carnivores—representing 16 canid and 18 felid species from six continents—we found strong evidence of a clade-level difference in species’ reliance on repeatedly used travel routeways. Across the global dataset, tracked canids had a 15% (±7 CI) greater density of routeways within their home ranges than did felids, rising to 33% (±16 CI) greater in landscapes shared with tracked felids. Moreover, comparisons within species across landscapes revealed broadly similar home range routeway densities despite habitat differences. On average, canids also reused their travel routeways more intensively than did felids, with hunting strategies and spatial contexts also contributing to the intensity of routeway usage. Collectively, our results suggest that key aspects of carnivore routeway-usage have an evolutionary component. Striking interspecific and clade-level differences in carnivores’ reliance on reused travel routeways within home ranges identify important ways in which the movement patterns of real-world predators depart from classical assumptions of predator-prey theory. Because such departures can drive key aspects of human-wildlife interactions and other encounter-based processes, continued investigations of the relationships between movement mechanisms and space use are critical.

Open science contributes to more rigorous and impactful science. However, little attention is often paid to the benefits that it provides to its users, such as project management and programming skills. Although not its primary objective, these skills may be considered additional benefits supporting the transition to open science practices. Drawing from international perspectives, this chapter will discuss skills that students develop explicitly or implicitly by engaging in open science and their benefits to careers within and outside of academia. It will also showcase examples of how engagement in open science is considered in (academic) hiring decisions, including ongoing debates and areas for (structural) improvement. Ultimately, this chapter will inform educators about the most important open science skills and provide insights into how to strategically build a resume to present open science-related skills convincingly to improve employability, including practical tips and resources.

In this paper, we explore the trajectory of the accumulation of unverifiable science in the literature under a variety of scenarios. We argue that without major changes in publication trends and research rigor, our ability to leverage science to solve humanity’s problems will be greatly compromised. We show that the accumulation of unverifiable science will soon reach a tipping point in which the rate of accumulation will far exceed our ability to correct the literature within practical constraints. Our models, while simplistic, are analogous to models of climate change, which warn of serious consequences if the current state of affairs is left unchecked. The simulation results indicate that addressing the accumulation of unverifiable science will require a combination of improving replicability rates (i.e. rigor), reducing research ’emissions’ (fewer articles but of better quality), and improved efforts to‘capture’ seriously flawed published papers.

Using data from a geopolitical forecasting tournament, Mellers et al. (2014) [Psychological strategies for winning a geopolitical forecasting tournament. Psychological Science, 25 , 1106–1115] concluded that forecasting ability was improved by allowing participants to work in teams and providing them with probability training. Here, we reevaluated Mellers et al.’s conclusions using an item response theory framework that models latent ability from forecasting choices. We found that the relationship between latent ability estimates and forecast accuracy differed from the interpretation of the original findings once key extraneous variables were statistically controlled. The best fit models across the first 2 years of the tournament included one or more extraneous variables that substantially eliminated, reduced, and, in some cases, even reversed the effects of the experimental manipulations of teaming and training on latent forecasting ability. We also show that latent traits associated with strategic responding can discriminate between superforecasters and non-superforecasters, making it difficult to identify the latent factors that underlie the superforecasters’ superior performance.

Recent years have seen a growing dissatisfaction with how academics and their scholarly work are evaluated, and a corresponding global proliferation of initiatives dedicated to assessment reform. A common theme across many of these initiatives is a call to center values, focusing on how incentives could be designed to better reward aspects like collaboration, equity, rigor, and transparency. While such values-based approaches have laid solid groundwork for academic institutions to think through and prioritize their values, we see a need for granular tools that can help institutions transform their values into actionable reforms. To that end, we present a framework, developed in part through workshops we ran at the 2023 Council of Graduate Departments of Psychology (COGDOP) Annual Meeting, the Association for Psychological Science (APS) Annual Convention, and the American Anthropological Association (AAA) Department Leaders Summer Institute. The framework includes 14 values (e.g. creativity, inclusivity, engagement, public good), and for each value, we outline some scoping considerations, representative academic activities or scholarly outputs, and possible behavioral indicators that could be incorporated into promotion and tenure evaluations. This framework is not exhaustive, and will likely vary depending on disciplinary or other contexts, but we we hope it will serve as a starting point and encourage institutions to tackle assessment reforms with a values-based lens.

Despite the common assumption that citations are indicative of an article’s scientific merit, increasing evidence indicates that citation counts are largely driven by variables unrelated to quality. In this article, we treat people’s decisions of what to cite as an instance of memory retrieval and show that observed citation patterns are well accounted for by a model of memory. The proposed exposure model anticipates that small alterations in factors that affect people’s ability to retrieve to-be-cited articles from memory early in their life cycle are magnified over time and can lead to the emergence of highly cited papers. This effect occurs even when there is no variation in the starting point exposure probabilities (i.e. when assuming a level playing field where all articles are treated equally and of equal ‘quality’), and is exacerbated by natural variation in retrievability of articles due to encoding. We discuss the implications of the model within the context of research evaluation and hiring, tenure and promotion decisions.

The biomedical sciences must maintain and enhance a research culture that prioritizes rigour and transparency. The US National Institute of Neurological Disorders and Stroke convened a workshop entitled ‘Catalyzing Communities of Research Rigor Champions’ that brought together a diverse group of leaders in promoting research rigour and transparency (identified as ‘rigour champions’) to discuss strategies, barriers and resources for catalyzing technical, cultural and educational changes in the biomedical sciences. This article summarizes 2 days of panels and discussions and provides an overview of critical barriers to research rigour, perspectives behind reform initiatives and considerations for stakeholders across science. Additionally, we describe applications of network science to foster, maintain and expand cultural changes related to scientific rigour and opportunities to embed rigourous practices into didactic courses, training experiences and degree programme requirements. We hope this piece provides a primer for the wider research community on current discussions and actions and inspires individuals to build, join or expand collaborative networks within their own institutions that prioritize rigourous research practices.

Colleges and universities largely exist to advance knowledge for the public good through research, teaching, and public service. Yet, for far too long academic incentive systems have been misaligned with the foundational values upon which universities were founded. Rather than reward work based on the substance of their work, researchers are often rewarded based on superficial "metrics" that promote quantity over quality and under-value research that addresses critical societal problems. Our motivation for creating this toolkit stems from the recognition that correcting this misalignment is necessary for promoting research integrity, restoring trust in science (and higher education), and building a more just society. This is a living document that we plan on updating and improving periodically, much like improving our assessment practices requires continual effort to improve. With that in mind, please treat as you would any draft document.

Using data from a geo-political forecasting tournament, Mellers et al. (2014) showed that forecast accuracy could be improved by allowing participants to work in teams and by providing participants with probability training. Here, we re-evaluate the results of Mellers et al. (2014) using an Item Response Theory framework and show that controlling for variation in key aspects of the methodology alters the interpretation of the original findings. Specifically, we compared the fit indices of seven models over the first two years of the tournament and three different ways of conditioning the data. In all cases, the best-fit model included one or more confounding variables, which substantially eliminated, reduced, and, in some cases, even reversed the observed effects on the Brier score. We also show that a confounding variable can discriminate between super and non-super forecasters, making it difficult to identify the latent factors that underlie the superforecasters’ superior performance.