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This paper focuses on the effects of entrepreneurial overconfidence at new venture creation. By analyzing Global Entrepreneurship Monitor data and using the theory of planned behavior as a framework, the study provides new evidence on the relative or absolute nature of overconfidence in entrepreneurial skills and the effect of overprecision on new venture creation. Overprecision of supporting beliefs is newly linked to venture creation and it is shown that nascent entrepreneurs’ overconfidence is based on a self-focusing attitude. The results confirm that overconfidence is not a single construct and highlights the differences between the forms of overconfidence habitually confused in the entrepreneurship literature.
Relative to dementia, little is known about informant bias in mild cognitive impairment (MCI). We investigated the influence of informant demographic and relational characteristics on reports of everyday functioning using the Functional Activities Questionnaire (FAQ).
Four thousand two hundred eighty-four MCI participants and their informants from the National Alzheimer’s Coordinating Center Uniform Data Set were included. Informants were stratified according to cohabitation, relationship, visit frequency, race/ethnicity, education, and sex. Informant-rated Mean FAQ score was compared across these groups using univariate general linear model analyses and post hoc tests. Interactions were tested between informant variables. The predictive contribution of informant variables to FAQ score was explored using hierarchical linear regression. Analyses covaried for participant cognition using a cognitive composite score, and for participant age, sex, and depression.
After controlling for participant cognition, depression, age, and sex, informant-rated FAQ scores varied significantly across all informant variables (p’s < .005, ηp2’s ≤ .033) except sex and visit frequency. FAQ scores were higher (more impaired) among informants who cohabitate with the participant, among paid caregivers, spouses, and adult children, and among informants with higher levels of education. Scores were lowest (less impaired) among Black/African American informants as compared to all other racial/ethnic groups.
Demographic and relational characteristics of informants influence the perception and reporting of instrumental activities of daily living in adults with MCI. As everyday functioning is crucial for differential diagnosis and treatment outcome measurement, it is important to be aware of sources of informant report discrepancies.
Portable haemoglobinometers have been used in order to estimate the prevalence of anaemia in diverse settings. However, few studies have been conducted to evaluate their performance in children of different age groups in distinct epidemiological contexts. To evaluate the reproducibility and reliability of a portable haemoglobinometer for the diagnosis of anaemia in children <5 years Hb was measured in the venous blood of 351 children <5 years by an automated system (standard method) and in three capillary blood samples, using a portable haemoglobinometer (HemoCue®; test method). The reproducibility of the device and of the test method was evaluated using the intraclass correlation coefficient (ICC) (Hb in its continuous form), κ and prevalence-adjusted bias-adjusted κ (PABAK) (categorised variable: anaemia: yes/no). For test method validation, Bland–Altman analyses were performed and sensitivity, specificity, accuracy rate, positive predictive value (PPV) and negative predictive values (NPV) were calculated. The haemoglobinometer presented good device reproducibility (ICC = 0·79) and reasonable method reproducibility (puncture, collection and reading) (ICC = 0·71). Superficial and fair agreement (κ) and good agreement (PABAK) were observed among the diagnoses obtained through the test method. The prevalence of anaemia was 19·1 and 19·7 % using the standard and the test method, respectively, with no statistically significant differences. The test method presented higher specificity (87·7 %) and NPV (88·3 %) than sensitivity (50·7 %) and PPV (49·3 %), and intermediary accuracy rate (57·8 %). HemoCue® showed good device reproducibility and reasonable method reproducibility, as well as good performance in estimating the prevalence of anaemia. Nevertheless, it showed a fair reliability and low individual diagnostic accuracy.
Research suggests that critical thinking skills are often surprisingly domain-specific. We survey the case histories of several Nobel Prize winners in the sciences to demonstrate that even extremely bright individuals can fall prey to bizarre ideas. These findings strongly suggest that intellectual brilliance and acceptance of weird ideas are not mutually incompatible. They also highlight the domain-specificity of critical thinking and the surprising independence of general intelligence from critical thinking. A number of cognitive errors, including bias blind spot and the senses of omniscience, omnipotence, and invulnerability; personality traits such as narcissism and excessive openness; and the “guru complex” may predispose highly intelligent individuals to disastrous critical thinking errors.
The political atmosphere on US college campuses is overwhelmingly left-leaning and liberal, with the vast majority of faculty self-identifying as socially progressive. Considerable research on cognitive biases has demonstrated the pervasive role of people’s attitudes, which act as filters during thinking and reasoning – particularly about politically-valenced topics. The prevalence of faculty from one side of the political spectrum coupled with the omnipresence of cognitive biases means that college campuses and the research done by their faculty runs the risk of favoring one side during what should, scientifically-speaking, be a process of fair and open inquiry. We discuss these phenomena and document numerous examples in which lack of genuine viewpoint diversity has spelled trouble for sound science. We advocate a more ideologically-diverse scientific workforce to better enable true diversity of thinking on key issues of our time.
As part of the study of the early medieval cemetery at Broechem (Belgium), human bones from 32 cremation graves have been dated through radiocarbon (14C) analysis. It was noted that many of the dates were not in accordance with the chronological ranges provided by the characteristics of the cultural artifacts deposited in the graves. In fact, the human bones were “older” than the artifacts. Subsequently, a number of animal bones (in all cases from domestic pigs) was radiocarbon dated, yielding dates that were more consistent with the information from the cultural artifacts than the human bones. The dates obtained on human and pig bones from the same grave often differed around 100 radiocarbon years. This paper tries to find an explanation for the pattern observed, concentrating on two hypotheses: aquatic reservoir versus old wood effects. The evaluation takes into account additional radiocarbon dates derived from charcoal fragments of the funeral pyre, from both short-lived and long-lived taxa. A conclusive explanation for the anomalous radiocarbon dates could not be reached but clear suggestions can be put forward for future experimental work that will without doubt shed more light upon the interpretational problems raised.
Information about the ideological positions of different political actors is crucial in answering questions regarding political representation, polarization, and voting behavior. One way to obtain such information is to ask survey respondents to place actors on a common ideological scale, but, unfortunately, respondents typically display a set of biases when performing such placements. Key among these are rationalization bias and differential item functioning (DIF). While Aldrich–McKelvey (AM) scaling offers a useful solution to DIF, it ignores the issue of rationalization bias, and this study presents Monte Carlo simulations demonstrating that AM-type models thus can give inaccurate results. As a response to this challenge, this study develops an alternative Bayesian scaling approach, which simultaneously estimates DIF and rationalization bias, and therefore performs better when the latter bias is present.
The Thomas Jefferson Center Annual Reports credit the Volker Fund for a founding grant and the Earhart Foundation for providing critical support to graduate students. The Rockefeller Foundation supported Nutter’s NBER Soviet growth project and provided Tullock’s initial fellowship at the TJC. The Earhart Fellowship program has been neglected in previous histories of this period, perhaps because it was decentralized. The Foundation selected faculty sponsors to award graduate fellowship to students of their choice. The chapter presents the history of the fellowship program by major departments over the whole of the foundation’s existence. Harvard, Berkeley, and Columbia had fellows a year before the University of Chicago but Earhart fellowships at those institutions declined over time while those at Chicago and Virginia survived. Thus, the association of the Earhart Foundation with Chicago seems to be a result of a survival bias. The number of sponsors or fellows who were president of the American Economic Association or Nobel laureates is also remarkable. Earhart funded Nutter’s “rational debate” series exemplifying government by discussion at the early Virginia School.
The frequency division multiple access (FDMA) strategy used in GLONASS causes inter-frequency phase bias (IFPB) and inter-frequency code bias (IFCB) between receivers from different manufacturers. The existence of IFPB and IFCB significantly increases the difficulties of fixing GLONASS ambiguity and limits the accuracy and reliability of GLONASS positioning. Moreover, the initial value of IFPB and IFCB may be unavailable or unreliable with the increasing number of receivers from different manufacturers in recent years. In this study, a real-time and reliable calibration algorithm of IFPB and IFCB based on multi-GNSS assistance is proposed by providing a fixed solution. Real-time IFPB rate and IFCB can be obtained using this algorithm without the initial IFPB and IFCB. The IFPB rate for all GLONASS satellites and IFCB for each GLONASS satellite are estimated due to different characteristics of IFPB and IFCB. IFPB calibration can be divided into constant and real-time IFPB calibrations to meet the different positioning requirements. Results show that constant IFPB rate has only 2 mm difference from the mean value of real-time IFPB rate. The IFPB rate and IFCB estimated by this algorithm have excellent stability, and the change in reference satellite cannot affect the results of IFPB rate and the stability of IFCB. The centimetre-level positioning results can be obtained using two calibration methods, and the positioning results with real-time calibration method are 10%–20% better than those with the constant calibration method. Under satellite-deprived environments, the improvements of multi-GNSS positioning accuracy with constant inter-frequency bias calibration gradually increase as the satellite cut-off elevation angle increases compared with GPS/BDS, which can reach up to 0·9 cm in the vertical direction.
This article considers recent ethical topics relating to medical AI. After a general discussion of recent medical AI innovations, and a more analytic look at related ethical issues such as data privacy, physician dependency on poorly understood AI helpware, bias in data used to create algorithms post-GDPR, and changes to the patient–physician relationship, the article examines the issue of so-called robot doctors. Whereas the so-called democratization of healthcare due to health wearables and increased access to medical information might suggest a positive shift in the patient-physician relationship, the physician’s ‘need to care’ might be irreplaceable, and robot healthcare workers (‘robot carers’) might be seen as contributing to dehumanized healthcare practices.
The US Supreme Court has the power of certiorari. It may pick its fights. As a beneficial side effect, the court may allocate its resources, in particular the time and energy the justices spend on a case, to worthy causes. In economic parlance, this discretion makes the court more efficient. Efficiency comes at a political cost, though. This discretion also gives the court political power. It may direct its verdict to causes that are politically most relevant, or it may put an issue on the political agenda. Officially German constitutional law does not have certiorari. The Constitutional Court must decide each and every case that is brought. Yet over time the court has crafted a whole arsenal of more subtle measures for managing the case load. This paper shows that it uses these tools to engage in its version of allocating resources to cases. It investigates whether the ensuing efficiency gain comes at the cost of biasing the court’s jurisprudence. The paper exploits a new comprehensive data set. It consists of all (mostly only electronically) published cases the court has heard in 2011. While the data is rich, in many technical ways it is demanding. The paper uses a factor analysis to create a latent variable: to which degree has the court taken an individual case seriously? It then investigates whether observed indicators for bias explain this latent variable. Since the paper essentially investigates a single (independent) case, in statistical terms the findings are to be interpreted with caution. The paper can only aim at finding smoking guns.
Invalid responding is an important consideration in mental health assessment. Given that most assessment data are gathered from self-report methods, accurate diagnostic and clinical impressions can be compromised by various forms of response bias. In this chapter, we review the ways in which evaluations of psychopathology, neurocognitive symptoms, and medical/somatic presentations can be compromised due to noncredible responding and invalidating test-taking approaches. We cover a variety of strategies and measures that have been developed to assess invalid responding. Further, we discuss evaluation contexts in which invalid responding is most likely to occur. We conclude with some remarks regarding cultural considerations as well as how technology can be incorporated into the assessment of response bias.
Fully randomized conjoint analysis can mitigate many of the shortcomings of traditional survey methods in estimating attitudes on controversial topics. This chapter explains how we applied conjoint analysis at seven universities and describes the population of participants in our experiments.
Given the accelerating pace of information available in today’s world, our ability to be able to reflect critically on this information is more important today than ever before; but with the growth of social media and its unfortunate consequences – “fake news,” “post-truth,” and “truth decay” – critical reflection has become harder and harder to do. This apparent paradox, why “facts” and “evidence” seem to have so little effect on rational behavior, is explored, along with the research evidence on the self-reinforcing nature of confirmation bias and its sequelae, belief persistence, polarization, and tribalism.
The belief that a relationship partner values and promotes one’s welfare is central to many theories of interpersonal relationships. In this chapter, we review research on accuracy and bias in these perceptions of benevolence and their implications for relationship maintenance. A key conclusion emerging from this literature is that people’s perceptions of their relationship partners’ benevolence are both accurate and biased. Suggesting the operation of a confirmation bias, people’s chronic and generalized beliefs regarding other people’s benevolence appear to bias perceptions of partners’ benevolence within specific relationships. Suggesting the operation of a motivated wishful thinking bias, people’s desires to maintain close relationships with particular partners also bias perceptions of those partners’ benevolence. Despite these biases, there is also evidence for accuracy in perceptions of benevolence. Each of these processes, in turn, appears to shape people’s willingness to enact relationship maintenance behaviors. Suggested directions for future research are described.
Debates over diversity on campus are intense, they command media attention, and the courts care about how efforts to increase diversity affect students’ experiences and attitudes. Yet we know little about what students really think because measuring attitudes on politically charged issues is challenging. This book adopts an innovative approach to addressing this challenge.
An integration is offered of the book’s previous chapters, shifting from a review of prevailing theories and empirical evidence to a more practical set of recommendations. How might I become a better deep learner? And, how might I encourage deep learning in others? Principles for cultivating a deep learning mindset include: (1) pay attention; (2) confront your biases; (3) engage the tensions; (4) maintain a humble curiosity; (5) see complexity everywhere and don’t let it scare you; (6) learn how to learn with others; (7) harness the power of politics; (8) invite disorientation through aesthetic experience; (9) engage in thought leadership.
The evidence for preference biases is very often flawed, incomplete, or misinterpreted. For example, inconsistent rates of time discount are largely eliminated when considered relative to the individual’s perception of time. Preference reversals in real time from patient to impatient behavior occur only in a minority of cases. Time inconsistency, when it occurs, need not be associated with actual harms to decision-makers. Evidence for the existence of endowment effects is problematic. Gaps between willingness to pay and willingness to accept have no normative significance. The evidence for impact bias is confused and weak, and to the extent that it occurs, its function has eluded most analysts. In addition to these concerns, we find that the preferences typically treated as normatively superior by behavioral paternalists are often implicated by biases as well.
Paternalist policymakers face a severe knowledge problem that is analogous to the knowledge problem faced by central planners. They do not and often cannot possess the kind of local and tacit knowledge needed to craft policy interventions that reliably improve human welfare. We provide a taxonomy of types of knowledge that paternalist planners need but typically do not have: true preferences, extent of bias, self-debiasing and small-group debiasing, dynamic impacts on self-regulation, counteracting behaviors, bias interactions, and population heterogeneity. We also critique two leading efforts to surmount knowledge problems of behavioral paternalism: the augmented revelatory frame approach and unified behavioral revealed preference.