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As societies become more polarized, there is increasing pressure for business leaders to have a sense of purpose and to make moral decisions. Being a good leader requires both a keen understanding of the realities of human decision making as well as an analysis of what is right and wrong. This book integrates lessons from three intellectual traditions – psychology, philosophy, and political economy – to guide readers on a journey to rigorously explore their values and decision making. The authors begin by examining people's intuitions about right and wrong. They then clarify principles that embody these intuitions and help readers engage with others whose intuitions or principles differ from their own. Ultimately, this book teaches readers how to be strategic as they lead with their values: as individuals, as designers of organizations, and as businesspeople interacting with societal institutions.
Publication bias and p-hacking are threats to the scientific credibility of experiments. If positive results are more likely to be published than null results conditional on the quality of the study design, then effect sizes in meta-analyses will be inflated and false positives will be more likely. Publication bias also has other corrosive effects as it creates incentives to engage in questionable research practices such as p-hacking. How can these issues be addressed such that the credibility of experiments is improved in political science? This chapter discusses seven specific solutions, which can be enforced by both formal institutions and informal norms.
Background: Healthcare-associated infections (HAIs) are a major global threat to patient safety. Systematic surveillance is crucial for understanding HAI rates and antimicrobial resistance trends and to guide infection prevention and control (IPC) activities based on local epidemiology. In India, no standardized national HAI surveillance system was in place before 2017. Methods: Public and private hospitals from across 21 states in India were recruited to participate in an HAI surveillance network. Baseline assessments followed by trainings ensured that basic microbiology and IPC implementation capacity existed at all sites. Standardized surveillance protocols for central-line–associated bloodstream infections (CLABSIs) and catheter-associated urinary tract infections (CAUTIs) were modified from the NHSN for the Indian context. IPC nurses were trained to implement surveillance protocols. Data were reported through a locally developed web portal. Standardized external data quality checks were performed to assure data quality. Results: Between May 2017 and April 2019, 109 ICUs from 37 hospitals (29 public and 8 private) enrolled in the network, of which 33 were teaching hospitals with >500 beds. The network recorded 679,109 patient days, 212,081 central-line days, and 387,092 urinary catheter days. Overall, 4,301 bloodstream infection (BSI) events and 1,402 urinary tract infection (UTI) events were reported. The network CLABSI rate was 9.4 per 1,000 central-line days and the CAUTI rate was 3.4 per 1,000 catheter days. The central-line utilization ratio was 0.31 and the urinary catheter utilization ratio was 0.57. Moreover, 3,542 (73%) of 4,742 pathogens reported from BSIs and 868 (53%) of 1,644 pathogens reported from UTIs were gram negative. Also, 1,680 (26.3%) of all 6,386 pathogens reported were Enterobacteriaceae. Of 1,486 Enterobacteriaceae with complete antibiotic susceptibility testing data reported, 832 (57%) were carbapenem resistant. Of 951 Enterobacteriaceae subjected to colistin broth microdilution testing, 62 (7%) were colistin resistant. The surveillance platform identified 2 separate hospital-level HAI outbreaks; one caused by colistin-resistant K. pneumoniae and another due to Burkholderia cepacia. Phased expansion of surveillance to additional hospitals continues. Conclusions: HAI surveillance was successfully implemented across a national network of diverse hospitals using modified NHSN protocols. Surveillance data are being used to understand HAI burden and trends at the facility and national levels, to inform public policy, and to direct efforts to implement effective hospital IPC activities. This network approach to HAI surveillance may provide lessons to other countries or contexts with limited surveillance capacity.
Resistance to colistin, a last resort antibiotic, has emerged in India. We investigated colistin-resistant Klebsiella pneumoniae(ColR-KP) in a hospital in India to describe infections, characterize resistance of isolates, compare concordance of detection methods, and identify transmission events.
Retrospective observational study.
Case-patients were defined as individuals from whom ColR-KP was isolated from a clinical specimen between January 2016 and October 2017. Isolates resistant to colistin by Vitek 2 were confirmed by broth microdilution (BMD). Isolates underwent colistin susceptibility testing by disk diffusion and whole-genome sequencing. Medical records were reviewed.
Of 846 K. pneumoniae isolates, 34 (4%) were colistin resistant. In total, 22 case-patients were identified. Most (90%) were male; their median age was 33 years. Half were transferred from another hospital; 45% died. Case-patients were admitted for a median of 14 days before detection of ColR-KP. Also, 7 case-patients (32%) received colistin before detection of ColR-KP. All isolates were resistant to carbapenems and susceptible to tigecycline. Isolates resistant to colistin by Vitek 2 were also resistant by BMD; 2 ColR-KP isolates were resistant by disk diffusion. Moreover, 8 multilocus sequence types were identified. Isolates were negative for mobile colistin resistance (mcr) genes. Based on sequencing analysis, in-hospital transmission may have occurred with 8 case-patients (38%).
Multiple infections caused by highly resistant, mcr-negative ColR-KP with substantial mortality were identified. Disk diffusion correlated poorly with Vitek 2 and BMD for detection of ColR-KP. Sequencing indicated multiple importation and in-hospital transmission events. Enhanced detection for ColR-KP may be warranted in India.
Politicians bequeath an important legacy after they leave office: the public’s memories of their time in office. Indeed, the media often discuss legacy concerns as a key motivation of politicians. Yet, there has been little empirical analysis of how politicians’ legacies are interpreted and used by the mass public. Analyzing millions of comments from online discussion forums, we show that citizens frequently mobilize memories of past politicians in their discussions of current events. A randomized survey experiment rationalizes such invocations of past politicians: they bolster the persuasiveness of contemporary arguments—particularly bad ones—but only when made in the context of a policy domain specifically associated with a past politician. Our findings suggest that politicians have a strong interest in cultivating a positive, broad, and enduring legacy because memories of them influence policy debates long after they leave office.
Previous research has emphasized corporate lobbying as a pathway
through which businesses influence government policy. This article
examines a less-studied mode of influence: private regulation,
defined as voluntary efforts by firms to restrain their own
behavior. We argue that firms can use modest private regulations as
a political strategy to preempt more stringent public regulations.
To test this hypothesis, we administered experiments to three groups
that demand environmental regulations: voters, activists, and
government officials. Our experiments revealed how each group
responded to voluntary environmental programs (VEPs) by firms.
Relatively modest VEPs dissuaded all three groups from seeking more
draconian government regulations, a finding with important
implications for social welfare. We observed these effects most
strongly when all companies within an industry joined the voluntary
effort. Our study documents an understudied source of corporate
power, while also exposing the limits of private regulation as a
strategy for influencing government policy.
Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88) presented a critique of our recently published paper in Cell Reports entitled ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ (Lam et al., Cell Reports, Vol. 21, 2017, 2597–2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229–237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from ‘inflation in the FDR [false discovery rate]’, as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84–88), and are not ‘more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence’.
Although Boyer & Petersen's (B&P's) cataloguing of and evolutionary explanations for folk-economic beliefs is important and valuable, the authors fail to connect their theories to existing explanations for why people do not think like economists. For instance, people often have moral intuitions akin to principles of fairness and justice that conflict with utilitarian approaches to resource allocation.
Weighting techniques are employed to generalize results from survey experiments to populations of theoretical and substantive interest. Although weighting is often viewed as a second-order methodological issue, these adjustment methods invoke untestable assumptions about the nature of sample selection and potential heterogeneity in the treatment effect. Therefore, although weighting is a useful technique in estimating population quantities, it can introduce bias and also be used as a researcher degree of freedom. We review survey experiments published in three major journals from 2000–2015 and find that there are no standard operating procedures for weighting survey experiments. We argue that all survey experiments should report the sample average treatment effect (SATE). Researchers seeking to generalize to a broader population can weight to estimate the population average treatment effect (PATE), but should discuss the construction and application of weights in a detailed and transparent manner given the possibility that weighting can introduce bias.
Although there are compelling theoretical reasons to believe that unequal political representation in a legislature leads to an unequal distribution of funds, testing such theories empirically is challenging because it is difficult to separate the effects of representation from the effects of either population levels or changes. We leverage the natural experiment generated by infrequent and discrete census apportionment cycles to estimate the distributional effects of malapportionment in the U.S. House of Representatives. We find that changes in representation cause changes in the distribution of federal outlays to the states. Our method is exportable to any democratic system in which reapportionments are regular, infrequent, and nonstrategic.
Challenging conventional wisdom, previous research in South Asia and the Middle East has shown that poverty and exposure to violence are negatively correlated with support for militant organizations. Existing studies, however, provide evidence consistent with two potential mechanisms underlying these relationships: (1) the direct effects of poverty and violence on attitudes toward militant groups and (2) the psychological effects of perceptions of poverty and violence on attitudes. Isolating whether the psychological mechanism is an important one is critical for building theories of mass responses to political violence. We conducted a series of original, large-scale survey experiments in Pakistan (n=16,279) in which we randomly manipulated perceptions of both poverty and violence before measuring support for militant organizations. We find evidence that psychological perceptions do in part explain why the poor seem to be less supportive of militant political groups.
The accuracy of published findings is compromised when researchers fail to report and adjust for multiple testing. Preregistration of studies and the requirement of preanalysis plans for publication are two proposed solutions to combat this problem. Some have raised concerns that such changes in research practice may hinder inductive learning. However, without knowing the extent of underreporting, it is difficult to assess the costs and benefits of institutional reforms. This paper examines published survey experiments conducted as part of the Time-sharing Experiments in the Social Sciences program, where the questionnaires are made publicly available, allowing us to compare planned design features against what is reported in published research. We find that: (1) 30% of papers report fewer experimental conditions in the published paper than in the questionnaire; (2) roughly 60% of papers report fewer outcome variables than what are listed in the questionnaire; and (3) about 80% of papers fail to report all experimental conditions and outcomes. These findings suggest that published statistical tests understate the probability of type I errors.
That citizens engage in retrospective voting is widely established in the literature. But to what extent is retrospection affected by the expectations that leaders set in advance? We develop a theoretical framework of how expectation setting affects voters’ retrospective evaluations of incumbent performance. To test the theory, we conduct a series of between-subjects experiments in which we independently manipulate both expectation setting and the eventual outcome. In domains where politicians have practical authority, or direct influence over outcomes, setting high expectations incurs a cost in public support if the projected outcome is not attained. The same is true in domains where politicians have theoretical authority, or limited influence, but where expectation setting sends a signal about the leader’s judgment. However, in domains where politicians have neither practical nor theoretical authority, setting high expectations is unambiguously beneficial, implying that optimism is valued by voters as a personality disposition.
How do citizens attribute blame in the wake of government failure? Does partisanship bias these attributions? While partisan cues may serve as useful guides when citizens are evaluating public policies, those cues are likely to be less informative and more distortionary when evaluating government performance regarding a crisis. We address these questions by examining blame attributions to government appointees for the 9/11 terrorist attacks. We implement an experimental design in a nationally representative survey that builds on previous work in two ways: (1) we manipulate party labels for the same officials in a real-world setting by considering appointees who were nominated at different times by presidents of different parties; and (2) we examine how domain relevance moderates partisan bias. We find that partisan bias in attributions is strongest when officials are domain relevant, a finding that has troubling implications for representative democracy.
Scholars have argued that childhood experiences strongly impact political attitudes, but we actually have little causal evidence since external factors that could influence preferences are correlated with the household environment. We utilize a younger sibling’s gender to isolate random variation in the childhood environment and thereby provide unique evidence of political socialization. Having sisters causes young men to be more likely to express conservative viewpoints with regards to gender roles and to identify as Republicans. We demonstrate these results in two panel surveys conducted decades apart: the Political Socialization Panel (PSP) and the National Longitudinal Survey of Youth (NLSY). We also use data collected during childhood to uncover evidence for a potential underlying mechanism: families with more female children are more likely to reinforce traditional gender roles. The results demonstrate that previously understudied childhood experiences can have important causal effects on political attitude formation
The empirical study of spatial issue voting has experienced a resurgence in recent years due to advances in data collection and research design. Grynaviski and Corrigan make several important contributions to this literature. In this note, we comment on one of Grynaviski and Corrigan's recommendations—to not include a main effect for issue importance when estimating models assessing the interactive relationship between importance and policy proximity. According to the authors, including the main importance term is incorrect because it is not necessary in representing a scale-invariant functional form under some assumptions and is insufficient under others. In deriving their reduced-form expression, the authors produce a model that is unintuitive and inappropriate for most data. Moreover, the restrictions Grynaviski and Corrigan impose on their model can produce perverse empirical predictions. We show that a model including main effect terms for importance is indeed scale invariant and that inclusion of the main importance term is necessary for scale invariance with respect to partial utility functions.
Economic interests and party identification are two key, long-standing factors that shape people’s attitudes on government policy. Recent research has increasingly focused on how short-term communication effects (e.g., issue framing, media priming) also influence public opinion. Rather than posit that political attitudes reflect one source of considerations more than another, we argue that the two interact in a significant and theoretically predictable manner. To explore this claim, we examine the American public’s attitudes towards the government’s response to the financial crisis of 2008. We designed three survey experiments conducted on a large national sample, in which we examine the influence of (1) group-serving biases, (2) goal framing, and (3) threshold sensitivity. We find that economic standing and partisanship moderate the impact of communication effects as a function of their content. Our results demonstrate how people’s sensitivity to peripheral presentational features interacts with more fundamental dispositions in shaping attitudes on complex policy issues.
Do voters effectively hold elected officials accountable for policy decisions? Using data on natural disasters, government spending, and election returns, we show that voters reward the incumbent presidential party for delivering disaster relief spending, but not for investing in disaster preparedness spending. These inconsistencies distort the incentives of public officials, leading the government to underinvest in disaster preparedness, thereby causing substantial public welfare losses. We estimate that $1 spent on preparedness is worth about $15 in terms of the future damage it mitigates. By estimating both the determinants of policy decisions and the consequences of those policies, we provide more complete evidence about citizen competence and government accountability.
Does complete public financing of campaigns enhance electoral competition? Arizona and Maine implemented similar clean elections programs for state-level races in 2000, providing an opportunity to examine the consequences of public financing. Employing two measures of competitiveness, I find that clean elections programs in both states significantly increased competition in districts where challengers accepted public funding. These findings suggest that public monies do not simply attract low-quality challengers and that access to campaign funds is an important determinant of competitiveness. As a result, while public financing programs are not panaceas for uncompetitive elections, such programs can enhance competition in races where money is accepted.