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In this note, we provide direct evidence of cheating in online assessments of political knowledge. We combine survey responses with web tracking data of a German and a US online panel to assess whether people turn to external sources for answers. We observe item-level prevalence rates of cheating that range from 0 to 12 percent depending on question type and difficulty, and find that 23 percent of respondents engage in cheating at least once across waves. In the US panel, which employed a commitment pledge, we observe cheating behavior among less than 1 percent of respondents. We find robust respondent- and item-level characteristics associated with cheating. However, item-level instances of cheating are rare events; as such, they are difficult to predict and correct for without tracking data. Even so, our analyses comparing naive and cheating-corrected measures of political knowledge provide evidence that cheating does not substantially distort inferences.
Sustainability has become the privileged way businesses, NGOs, and governments think about actions they might take to remediate environmental problems and be good actors vis-à-vis natural resources and our shared climate. In turn, the way that sustainable actions are accounted for is in the language of “impacts” in which various accounting schemes seek to tabulate and communicate the degree to which some sustainable action has an effect in the world. The purpose of generating a quantifiable, representable impact is so that consumers might decide that it makes a company or product more worthwhile and more deserving of a consumer’s money on a market. On a market, a consumer has the ability to decide that other qualities (price, brand, convenience, etc.) could potentially outweigh good environmental action. The purpose of explaining all this is to show just how limited a utilitarian approach (one in which goods are measured, weighed, and seen as interchangeable) to fixing environmental problems is. What Archer demonstrates is that by tracking environmental action in terms of comparable, fungible impacts, one allows corporate actors to count their pollution or bad action, and continue to do it anyway, both masking it behind impact measures and abdicating any final responsibility to consumers. At the close of the paper, Archer offers a different way of thinking about sustainable environmental action, one that draws on various strands of indigenous thinking to illustrate what it would look like and how much more effective things would be if we understood good environmental action in terms of nonnegotiable values (in philosophy language, a “deontological” approach).
Chapter 3 offers an inventory of contributions to knowledge. In order to get started it is helpful to understand where one wishes to end up, i.e., what the completed study is intended to accomplish. We show that there are many ways to make your mark. Contributions may focus on (a) phenomena, (b) concepts, (c) data and measures, (d) causes, (e) mechanisms and frameworks, (f) research designs, or (g) empirical refinements and extensions.
Societal attitudes toward gender roles in the workplace and politics play a central part in theorizing on the difficulty women face in achieving political equality, but shortcomings in the available data have prevented direct examination of many implications of these theories. Drawing on recent advances in latent-variable modeling of public opinion and a comprehensive collection of survey data, we present the Public Gender Egalitarianism dataset to address this need: comparable estimates of the public's attitudes on gender equality in the public sphere across more than one hundred countries over time. These Public Gender Egalitarianism scores are strongly correlated with responses to individual survey items and with women's rates of participation in the labor force and corporate boards. We expect that the Public Gender Egalitarianism data will become an invaluable source for broadly cross-national and longitudinal research on the causes and consequences of collective attitudes toward gender equality in politics and the economy.
Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation’s course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation’s importance to risk assessment and clarification of the ontogeny of ASD.
Psychopathologists have failed to make significant progress toward understanding the causes of psychopathology. Despite the foundational importance of construct validity and measurement to our field, insufficient attention is paid to these concerns in the assessment of psychopathology vulnerabilities prior to their implementation in causal models. I review the current state of construct validity and measurement in psychopathology research, highlighting the lack of consensus regarding how we should define and measure vulnerability constructs. The limited capacity of open science practices to address these definitional and measurement challenges is discussed. Recommendations for progress are made, including the need for consensus agreement on (1) working definitions and (2) measures of vulnerability constructs. Other recommendations include (3) the need to incentivize ‘pre-clinical’ descriptive work focused on measurement development, (4) the formation of open-access databases designed to facilitate measurement evaluation and development, and (5) increased exploration of the use of novel technologies to facilitate the collection of high-quality measures of vulnerability.
Diversity's effect on violence is ambiguous. Some studies find that diverse areas experience more violence; others find the opposite. Yet conflict displaces and intimidates people, creating measurement challenges. We propose a novel indicator of diversity that circumvents these problems: the location of physical structures at disaggregated geographical levels. We introduce this solution in the context of the Troubles in Northern Ireland. Our data reveal a curvilinear relationship between diversity and conflict-related deaths, with the steepest increase at low diversity, driven by an increase in violence when our proxy for the Catholic proportion of the population rises from 0 to 20 percent. These patterns are consistent with a theory of group threat through exposure.
Critical ill patients are often haemodynamically unstable and accurate continuous monitoring is vital. Haemodynamic monitoring describes the measurement of the cardiovascular stability of the patient. Invasive blood pressure monitoring and central venous pressure monitoring provide a ‘real time’ measurement of the patients haemodynamic status and better allows clinicians to pre-emptively treat a patient before a more serious problem arises. Although invasive blood pressure monitoring has several advantages compared to non-invasive blood pressure monitoring, it is not without risk. Central venous pressure monitoring is similarly beneficial in that it supports the clinical decision making regarding a patient’s fluid status but also comes with additional risks. This chapter explores invasive blood pressure and central venous pressure monitoring in detail.
Research on the measurement of mental illness stigma and discrimination has grown rapidly in the past 15 years with a large number of measures developed. This chapter first defines mental illness stigma and discrimination and highlights the importance of using an appropriately targeted measurement strategy including consideration of key measurement principles such as content validity, context of use, and psychometric properties. Nine commonly used measures of perceived, experienced, and self -stigma and discrimination are then highlighted with measurement considerations summarized. We also discuss global and local measurement issues including translation and cross-cultural adaptation. Future directions for stigma and discrimination measurement research in mental illness stigma and discrimination are presented including the need to ensure that research includes consideration of complexity and variation in the experience of stigma and discrimination and that research is focused proportionately on communities that experience the most mental illness stigma and discrimination.
This study aimed to design and develop a self-report Disaster Literacy Scale (DLS) tool that could evaluate the knowledge and skills of an individual specific to Turkish society.
Item development, expert opinions, language control, pilot study and field testing processes were monitored in the measurement tool based on a conceptual model and recognition.
23 items were taken out since their common variance values (>0,508, >0.500, >0.500, >0.400, respectively) and factor load relationship (>0.46, >0.50, >0.50, >0.50 and >0.55, respectively) in the mitigation, preparedness, response and recovery phases of the Exploratory Factor Analysis were insufficient. The Cronbach Alpha value of the remaining 61 items in the Disaster Literary Scale is 0.954 and between 0.83-0.88 in lower dimensions. DLS scoring was standardized between 0-50 points.
The objectives, scopes, limitations and steps of the design and development process of the Disaster Literacy Scale were given in detail and made understandable for other societies. The Disaster Literacy Scale was developed as a self-report scale that could evaluate the knowledge and skills of Turkish society in disasters. The Disaster Literacy Scale is, therefore, expected to be accepted in more countries to improve the understanding of disaster literacy in different societies.
This chapter discusses the practice of measurement in psychological research. Here, where we cast doubt on the basic assumptions and endeavours underlying the act of measuring in mainstream psychology. Next, we introduce the processual alternative, which stresses the study of activity as situated and coupled with an environment. This chapter explains how a process approach to ‘measurement’ is thus fundamentally different from the standard one, and can remedy existing issues related to non-ergodicity and the ecological fallacy. These ideas are illustrated by means of the concept of intelligence, which is undoubtedly one of psychology’s show-pieces of measurement.
In this chapter, we discuss the measurement of working memory capacity and attention control. We begin by examining the origins of complex span measures of working memory capacity, which were created to better understand the cognitive processes underpinning language comprehension. We then review evidence for the executive attention theory of working memory, which places attention control at the center of individual differences in working memory capacity and fluid intelligence. Next, we describe the relationship between working memory capacity, attention control, and language comprehension, and discuss how maintenance and disengagement – two functions supported by the control of attention – contribute to performance across a range of cognitive tasks. We then identify factors that threaten the construct and criterion validity of measures of working memory capacity and attention control and detail the steps our laboratory has taken to refine these measures. We close by providing practical recommendations and resources to researchers who wish to use our new measures of working memory capacity and attention control in their work.
The capacity for temporary storage and manipulation of information, i.e., working memory (WM), was first reported to be related to vocabulary acquisition over 30 years ago (Daneman & Green, 1986, for general WM capacity; Gathercole & Baddeley, 1989 and Service, 1989, for phonological WM). Although a relationship with L2 vocabulary knowledge has been highlighted repeatedly among different populations, its strength seems to be a function of the aspect of WM (central executive, phonological short-term storage) and vocabulary knowledge (breadth, depth) investigated, and relatedly, the methodological choices made (e.g., measurement instruments, populations – children, adults). In our chapter, we aim to untangle these intersecting effects through a methodological lens. In order to do so, we discuss some published and unpublished results, comparing them according to their methodologies. We finish by proposing new perspectives on the interpretation of some of the commonly used tasks in WM and L2 vocabulary studies.
The relationship between working memory (WM) and second language (L2) reading comprehension has received considerable attention for nearly three decades. Although studies in this line of research generally report a small to moderate relationship between WM and L2 reading comprehension, comparison of studies remains challenging due to the lack of specification of the kind of comprehension under investigation (e.g., textbase, situation model) and the means of comprehension assessment. In addition, inconsistencies in the usage, scoring and analysis of WM measures further complicate the interpretation of findings across studies. Thus, in this chapter, we examine L2 reading-WM studies, paying particular attention to methodological considerations surrounding the use and scoring of WM tasks and the assessment of comprehension. We argue that methodological decisions can have non-trivial effects on this line of research and provide task recommendations based on current theorizing in reading
Psychological science constructs much of the knowledge that we consume in our everyday lives. This book is a systematic analysis of this process, and of the nature of the knowledge it produces. The authors show how mainstream scientific activity treats psychological properties as being fundamentally stable, universal, and isolable. They then challenge this status quo by inviting readers to recognize that dynamics, context-specificity, interconnectedness, and uncertainty, are a natural and exciting part of human psychology – these are not things to be avoided and feared, but instead embraced. This requires a shift toward a process-based approach that recognizes the situated, time-dependent, and fundamentally processual nature of psychological phenomena. With complex dynamic systems as a framework, this book sketches out how we might move toward a process-based praxis that is more suitable and effective for understanding human functioning.
The goal of this Element is to provide a detailed introduction to adaptive inventories, an approach to making surveys adjust to respondents' answers dynamically. This method can help survey researchers measure important latent traits or attitudes accurately while minimizing the number of questions respondents must answer. The Element provides both a theoretical overview of the method and a suite of tools and tricks for integrating it into the normal survey process. It also provides practical advice and direction on how to calibrate, evaluate, and field adaptive batteries using example batteries that measure variety of latent traits of interest to survey researchers across the social sciences.
Parceling is pre-modeling strategy to create fewer and more reliable indicators of constructs for use with latent variable models. Parceling is particularly useful for developmental scientists because longitudinal models can become quite complex and even intractable when measurement models of items are fit. In this Element the authors provide a detailed account of the advantages of using parcels, their potential pitfalls, as well as the techniques for creating them for conducting latent variable structural equation modeling (SEM) in the context of the developmental sciences. They finish with a review of the recent use of parcels in developmental journals. Although they focus on developmental applications of parceling, parceling is also highly applicable to any discipline that uses latent variable SEM.
Some people think wisdom is a stable and invariable individual disposition. Others view wisdom as deeply embedded in culture, experiences, and situations, and treat these features as mutually making up wisdom. What are the implications of each view for measurement, training, and the fundamental nature of wisdom itself? This chapter reviews evidence concerning the dispositional versus situational approaches to study wisdom. Even though main features of wisdom show some stability, there is also a profound and systematic variability in response to situational demands. By conceptualizing dispositions as a distribution of situation-specific responses, one can integrate dispositional and situational approaches to wisdom. Building on these insights, it is recommended to pay attention to contextual factors in measurement. Insight about contextual factors can also shed light on how to develop interventions for training wisdom.
To improve the validity of our comparative endeavors in ethno-politics, this piece re-examines the relationship between conceptual definitions, categories of classification used in large-N datasets, and thick description found through case studies. It does this through the lens of claims to autonomy by ethnic minorities, and in particular through a detailed comparative case study of what autonomy means as a programmatic goal for ethnic minority Hungarian elites in Romania and Slovakia. Three unexpected findings emerge which make the case for qualitative research to better inform the categories and variables used in large-N datasets (1) there is a weak relationship between the conceptual definitions of autonomy and the way it is coded in relevant datasets like the Minorities at Risk (MAR) dataset; (2) empirically, the Hungarian comparative case studies show that elites do not think of autonomy in the same way as the conceptual literature nor do their understandings of autonomy easily fit into the coding categories of datasets; (3) there is inconsistency across Hungarian minority elites in their own definitions of autonomy as well as the lack of distinctions between autonomy and other institutional arrangements. This raises issues of equivalence and ambiguity and I conclude with suggestions for better measurement.
Chapter 2 starts by placing experiments in the scientific process – experiments are only useful in the context of well-motivated questions, thoughtful theories, and falsifiable hypotheses. The author then turns to sampling and measurement since careful attention to these topics, despite being often neglected by experimentalists, are imperative. The remainder of Chapter 2 offers a detailed discussion of causal inference that is used to motivate an inclusive definition of “experiments.” The author views this as more than a pedantic exercise, as careful consideration of approaches to causal inference reveals the often implicit assumptions that underlie all experiments. The chapter concludes by touching on the different goals experiments may have and the basics of analysis. The chapter serves as a reminder of the underlying logic of experimentation and the type of mindset one should have when designing experiments. A central point concerns the importance of counterfactual thinking, which pushes experimentalists to think carefully about the precise comparisons needed to test a causal claim.