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Background: During online search queries, Google uses machine learning algorithms to provide frequently associated (“People Also Ask” [PAA]) questions with corresponding websites answering the ques...

The authors examine the problem of integrating urban sensing into engaged planning. The authors ask whether enhanced urban data and analysis can enhance resident engagement in planning and design, rather than hinder it, even when current urban planning and design practices are dysfunctional. The authors assess the outcomes of a planning and design effort in Charlottesville, Virginia, USA. Community-Centered Urban Sensing is a participatory urban sensing initiative developed by urban planners and designers, architects, landscape architects, and technologists at the University of Virginia to address the need for actionable information on the urban environment through community-engaged urban data collection and analysis. These findings address how technological urbanism moves from data to action, as well as its potential for marginalization. Finally, the authors discuss a conceptualization of smart and engaged planning that accounts for urban dysfunction. The smart cities paradigm should encompass modes and methods that function even when local urban systems are dysfunctional.

Schegloff described utterances such as “lemme ask you a question” as pre-questions, pre-pre’s or pre-delicates (Schegloff 1980). This paper provides a discussion of similar utterances in a specific institutional setting - political radio phone-in programs in Israel. The participants use these utterances in ways that are similar to Schegloff’s description. Yet, the pre-construction has additional institutional functions for the differing roles of the host and the caller. Hosts use these utterances to manage the interaction during overlaps as a means to secure an exclusive turn of talk following them. Callers use them infrequently at the beginning of their talk as story-prompts. Hosts may challenge this usage and the interactional role reversal. Regular callers can use the pre-constructions similarly to hosts. In this way, the pre-constructions in the Israeli radio phone-in programs are employed as interactional practices that relate and construct the roles in this institutional setting.

Personality not only plays essential roles in people's real lives, but also becomes an important factor for various online services. Traditional approaches to personality assessment usually ask users to answer a long list of questions and are thus not practical in many online systems. It is more desirable to use some universally observable data in the system to perform personality assessment. This paper reports a controlled study to investigate common mouse operations as a potential new type of data source for online personality assessment. We establish an elaborate personality-mouse behavior dataset from 146 subjects and propose kinematic and adjustment features to characterize mouse motion patterns. Statistical approaches and machine learning algorithms are employed to examine the connections between personality preferences and mouse motion features via correlation analysis, discernibility analysis, and personality recognition experiments. The results reveal some interesting expressions of cognitive personality perspectives reflected in mouse motion patterns, such as fast starting acceleration and better controller. Performance evaluation shows it is possible to recognize different personality preferences using mouse motion features with accuracies ranging from 60.6% to 78.3%. Our findings suggest a potential to use mouse operational behaviors as a new data source for personality assessment in various information systems.

A long-standing vision of indoor localization is to eliminate infrastructure and deployment costs. Recent innovations make it possible to enable device-to-device (D2D) localization while requiring multiple antennas for the systems. We ask the following question: can we localize the more generally-used single-antenna devices (e.g., IoT) using another single-antenna device (e.g., smartphone or smartwatch) in a smart environment where low-cost backscatter tags are widely deployed on walls or smart objects. In this paper, we present TagLoc, a light-weight system that enables device-to-device localization without relying on large antenna arrays. Our observation is that the reflected signals from the ambient smart environment can be exploited to eliminate the requirement of bulky antenna arrays that are unachievable for the simple-designed IoT devices. Specifically, TagLoc creates multiple direction signatures using backscatter arrays in smart environments. Then, the receiver can accurately estimate the direction signatures from the transmitter to the arrays and then localize the target by cooperating all tag arrays. We prototype TagLoc using two single-antenna Intel NUCs with off-the-shelf Intel 5300 WiFi cards and customized backscatter tags. The results show TagLoc can achieve robust performance in a real indoor environment with a median localization error of 0.82m.

Given a set of agents qualifying or disqualifying each other, group identification is the task of identifying a socially qualified subgroup of agents. Social qualification depends on the specific rule used to aggregate individual qualifications . The classical bribery problem in this context asks how many agents need to change their qualifications in order to change the outcome in a certain way. Complementing previous results showing polynomial-time solvability or NP-hardness of bribery for various social rules in the constructive (aiming at making specific agents socially qualified) or destructive (aiming at making specific agents socially disqualified) setting, we provide a comprehensive picture of the parameterized computational complexity landscape. Conceptually, we also consider a more fine-grained concept of bribery cost, where we ask how many single qualifications need to be changed, nonunit prices for different bribery actions, and a more general bribery goal that combines the constructive and destructive setting.

We bring attention to the important, but previously overlooked, role that seemingly mundane material objects in management classrooms can have in student team learning processes. Specifically, we consider how material objects can shape team learning processes. We conducted an inductive qualitative study exploring how teams in an undergraduate strategy course worked together using two types of material objects: (a) whiteboards and (b) flip charts. Our findings indicate that how students interact with material objects when participating in team learning processes is influenced by four properties: (a) object location (static, mobile), (b) record-keeping (temporary, permanent), (c) form (whole, segmented), and (d) sensory awareness. These properties were found to afford student teams different possibilities for using the object which, in turn, shapes team learning processes through the level of agency over embodied learning, the nature of problem-solving behaviors (expansionist or reductionist), and approach to conceptual understanding (synergistic or discrete). The study contributes nuanced insight into the role of material objects in team learning processes and has pedagogical and practical implications for researchers and educators.

Reachability queries ask whether a vertex can reach another vertex on large directed graphs. It is one of the most fundamental graph operators and has attracted researchers in both academics and industry to study it. The main technical challenge is to support fast reachability queries by efficient managing the three main costs: the index construction time, the index size and the query processing time on large/small and sparse/dense graphs. As real world graphs grow bigger in size, these problems remain open challenges that demand high performance solutions. In this paper, we propose a Multi-Dimensional Graph Labeling approach (called MGTag) to supporting fast reachability queries. MGTag is novel in three aspects. First, it recursively partitions a graph into multiple subgraphs with disjoint vertex sets, called non-shared graphs, and several inter-partition edges, called cross-edges. Second, we build a four-dimensional label - one dimension of layer, one dimension of non-shared graph and two dimensions of interval for each vertex in non-shared graphs. Finally, with the four-dimensional labeling scheme, we design algorithms to answer reachability queries efficiently. The extensive experiments on 28 large/small and dense/sparse graphs show that building the high dimensional index is quickly and the index size is also competitive compared with most of the state-of-the-art approaches. The results also show that our approach is more scalable and efficient than the state-of-the-art approaches in answering reachability queries on large/small and sparse/dense graphs.

Our ability to briefly retain information is often limited. Proactive Interference (PI) might contribute to these limitations (e.g., when items in recognition tests are difficult to reject after having appeared recently). In visual Working Memory (WM), spatial information might protect WM against PI, especially if encoding items together with their spatial locations makes item-location combinations less confusable than simple items without a spatial component. Here, I ask (1) if PI is observed for spatially distributed items, (2) if it arises among simple items or among item-location combinations, and (3) if spatial information affects PI at all. I show that, contrary to views that spatial information protects against PI, PI is reliably observed for spatially distributed items except when it is weak. PI mostly reflects items that appear recently or frequently as memory items, while occurrences as test items play a smaller role, presumably because their temporal context is easier to encode. Through mathematical modeling, I then show that interference occurs among simple items rather than item-location combinations. Finally, to understand the effects of spatial information, I separate the effects of (a) the presence and (b) the predictiveness of spatial information on memory and its susceptibility to PI. Memory is impaired when items are spatially distributed, but, depending on the analysis, unaffected by the predictiveness of spatial information. In contrast, the susceptibility to PI is unaffected by either manipulation. Visual memory is thus impaired by PI for spatially distributed items due to interference from recent memory items (rather than test items or item-location combinations).

Young people are marching around the globe to ask for measures against climate change and to protect the environment. Using novel survey data, we ask who participates in such powerful movements and what can be learned from our findings. The survey was conducted in German and is based on answers from more than 600 participants. We find that survey respondents are less likely to participate in climate marches like “Fridays for Future” in case they trust more in (large) corporations suggesting a link between trust and climate activism. We also ask whether worries about climate change or attitudes towards more environmentally friendly behavior match their participation frequency in climate marches. Results reveal that respondents being more worried about climate change or the environment tend to participate more often in marches addressing these concerns. Similarly, participation in climate marches correlates positively with acting environmentally sustainable. Hence, our findings might be relevant for corporations in case they want to keep the support of young customers participating in climate marches.

In this paper, we provide a new Markovian-type model for stock price trend analysis at the transaction level, and illustrate its use for trading in conjunction with a controller which makes buy and sell decisions. Central to our formulation is a sequence of i.i.d. random variables T_k which corresponds to the number of transactions between reversals in price direction. For a trader, this is an important indicator of the duration of a trend. For processes with large T_k, there is an incentive to try and capitalize by buying stock when a temporary trend is up and selling when it is down. The extent to which this is possible is determined by a model parameter p_e, called the probability of efficiency, which indicates the likelihood that the bid, ask and current price are such that one can seamlessly enter or exit the market without slippage. The degree to which a trader can exploit trending behavior is quantified in our main result which provides the expected value of the trading gain resulting from a strategically constructed feedforward switching controller. The paper also includes an example illustrating application of the theory using historical data.

Many service providers explicitly ask customers for a tip. This may create social pressure, thus resulting in lower tips. Building on the theory of psychological reactance, we propose that an explicit request to tip has a detrimental impact on tip size. Across two studies, a field experiment and an online experiment, we test this effect and examine how the physical presence of the server moderates this relationship. We find that an explicit request to tip negatively affects tip size, while server’s physical presence alleviates this effect. The findings also show that social pressure hampers perceived control, which in turn has a detrimental effect on tip size. In light of these findings, service providers might want to revisit their strategies to enhance tipping.

Response conflicts occur when the correct goal-congruent response is weaker than an alternative but incorrect response. To overcome response conflicts, the stronger response has to be inhibited, making the study of response conflicts an important research topic in higher order cognition. Response conflicts often result in conflict interference-an increase in error rates and response times. Here, we ask whether an invertebrate-the ant, Lasius niger-can solve such response conflicts and, if so, whether it suffers from conflict interference. We also ask whether ants show congruency sequence effects, where subjects show transiently reduced conflict inference when conflicts repeat. We developed task-mimicking aspects of the Stroop color-word test, in which ants must learn to follow a neutral cue (a scent) on a Y maze but ignore a dominant and innately meaningful signal (a pheromone trail). The pheromone can be congruent with the scent cue (lead to the same maze arm) or be incongruent. Both accuracy and task-solving latency suffered when the information sources were incongruent. There was no evidence of congruency sequence effects. Because of limitations of the experimental design, we cannot rule out that insects would also show a congruency sequence effect under a different experimental paradigm. Although the methodology is not directly comparable to human studies, the presence of clear conflict interference suggests parallels between insect and human information processing, in spite of completely different brains. This powerful and straightforward methodology opens the possibility of exploring conflict interference in the presence of prepotent response tendencies in an invertebrate model. We hope this work encourages the field of response competition to use the vast literature on response competition in animal behavior studies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Iovino, La’O and Mascarenhas (forthcoming) ask two important questions regarding the optimal conduct of monetary policy: Should the central bank’s policy depend on information the central bank has that is not available to markets? And should the central bank disclose information that it has but market participants do not? Iovino, La’O and Mascarenhas answer these questions using a simple, stylized model with one-period price stickiness. They show that efficient equilibria can be sustained regardless of whether policy depends on the central bank’s information and regardless of its disclosure policy. We explain the logic behind their irrelevance result and show that if restrictions are imposed on equilibria, then monetary policy should in general depend on the central banks information. Finally, we offer some speculative answers to their questions and discuss the sense in which policy is converging towards theory.

The access to increasing volumes of scientific and clinical data, particularly with the implementation of electronic health records, has reignited an enthusiasm for artificial intelligence and its application to the health sciences. This interest has reached a crescendo in the past few years with the development of several machine learning and deep learning based medical technologies. The impact to research and clinical practice within gastroenterology and hepatology has already been significant, but the near future promises only further integration of artificial intelligence and machine learning into this field. The concepts underlying artificial intelligence and machine learning initially seem intimidating, but with increasing familiarity they will become essential skills in every clinician's toolkit. In this Review, we provide a guide to the fundamentals of machine learning, a concentrated area of study within artificial intelligence that has been built upon a foundation of classical statistics. The most common machine learning methodologies, including those involving deep learning, are also described.

In-band full-duplex (IBFD) technology is promised to deliver us from the scarcity of spectral resources as well as create novel multifunction wireless systems [1] . This concept was initially investigated in the 1960s for continuous-wave radar applications [2] , and, in the past decade, it has undergone a shift in research toward communications [3] – [7] and converged RF systems [8] , [9] . Since 2010, more than 600 IEEE publications alone have focused on at least one aspect of the technology, including more than 400 conference papers, 200 journal articles, and 20 magazine features [10] . After digesting these numbers, it is fair to ask: Why has IBFD functionality not been incorporated into a wireless standard yet?

In sample surveys, when we need information regarding rare sensitive issues which people often do not prefer to share with others. In such situations this is also awkward for interviewers to ask the direct questions related to confidential and private matters of interviewees. An approach towards the open queries about sensitive issues generally results in the high non-response rates or misleading answers. The aim of this paper is to develop an effective randomized response model to overcome with these types of challenges arising due to sensitive nature of characteristic under study. In this paper we have proposed three-stage randomized response model for estimating mean number of individuals who possessed rare sensitive attribute which makes use of Poisson distribution. The properties of the proposed estimation procedures have been deeply examined when the parameter of a rare unrelated attribute is known as well as unknown. Privacy protection of respondents is also an equally important matter of concern. So measure of privacy protection for the proposed randomized response model has also been examined. Empirical studies are performed to support the theoretical results, which show the dominance of the proposed estimators over well-known contemporary estimators. From the findings of this study we may conclude that proposed randomized response model is rewarding in terms of percent relative efficiencies and privacy protection and may be recommended to survey practitioners for real life applications.

This article focuses on conceptions and representations of political participation. It is based on ethnographic research of a civics course that a multicultural NGO designed for young people from different racialized and ethnic minorities in Finland. We ask how political participation is conceptualized in such efforts to 'engage' or 'empower' 'marginalized' young people, what opportunities for political participation these practices present and how young people make use of them. We draw on new citizenship theory, which focuses on lived and acted citizenships and practices of mundane political agency. Our analytical focus is on performative acts and processes, and how these may transform conventions. Thus, we examine the political inherent in young people's actions and tackle the difficulty in recognizing young people's political activeness and agency. The young people on the civics course actively took the space provided for them and performed political participation. Adults often failed to recognize this, leading us to question what, in the adults' eyes, counts as acts and sites of political participation. We conclude that recognizing young people as political agents not only requires access and resources, but also negotiation of what is seen as political participation and what it can entail.

Although people are generally motivated to perform well at work, there is often ambiguity regarding whether they are meeting their organization’s standards. As such, people often seek feedback from others. To date, feedback-seeking research has emphasized the feedback seeker, identifying traits and circumstances associated with feedback seeking, whereas far less is known about this process from the feedback source’s point of view. However, we expect that feedback sources will vary in their willingness to allocate effort toward delivering feedback. Specifically, integrating the cost-value framework of feedback with self-regulatory theories of goal prioritization, we predict that effort allocated toward a feedback episode is determined by the feedback source’s perceptions of the feedback seeker’s motives for seeking feedback. Across two complementary studies, we found perceived instrumental motives (i.e., a desire to improve one’s performance) to be positively related to the amount of effort put toward delivering feedback, and perceived image enhancement motives (i.e., a desire to impress the feedback source) to be negatively related to effort allocation. Importantly, Study 1 was a field study in which managers were asked to report on a recent episode in which a subordinate had sought their feedback, and Study 2 used an experimental design in which feedback-seeking motives were manipulated. Thus, the current research makes an important contribution to the literature by considering the often overlooked role that the feedback source plays in the feedback process. Moreover, triangulation of both field and experimental data enhances both the external and internal validity of our conclusions.

For decades, research on the relationship between environmental sustainability and firm performance focused on determining whether the effect of the former on the latter was positive or negative. That potentially controversial approach had driven mainstream research to ask two focal questions: Does it pay to be green? and Does it cost to be green? Recent papers have explored a curvilinear effect (i.e., U-shaped and inverted U-shaped) by tackling another question: When does it pay to be green? These efforts, however, have either oversimplified the complex linkage between these two things into a linear relationship or confined the complexity within a formatted frame. This paper overcomes these shortfalls by exploring the holistic effect of environmental sustainability on firm performance, contingent upon corporate reputation. In conjunction with direct effect analysis, this paper uniquely explores the synergistic effect of environmental sustainability and corporate reputation on performance. In addition to detecting the nonlinear synergy pattern, we found that the synergy effect is asymmetric. Specifically, the effect is complementary for low-reputation firms but substitutive for high-reputation firms. In addition to its theoretical contributions and pragmatic implications, this paper uniquely presents PROCESS-Neural network as a promising analytic paradigm.

Voice assistants offer users access to an increasing variety of personalized functionalities. Researchers and engineers who build these experiences rely on various signals from users to create the machine learning models powering them. One type of signal is explicit feedback. While collecting explicit user feedback in situ via voice assistants would help improve and inspect the underlying models, from a user perspective it can be disruptive to the overall experience, and the user might not feel compelled to respond. However, careful design can help alleviate the friction in the experience. In this paper, we explore the opportunities and the design space for voice assistant explicit feedback elicitation. First, we present four usage categories of explicit feedback in situ for model evaluation and improvement, derived from interviews with machine learning practitioners. Then, using realistic scenarios generated for each category, we conducted an online study to evaluate multiple voice assistant designs. Our results reveal that when the voice assistant is introduced as a learner or a collaborator, users were more willing to respond to its request for feedback and felt less disruptive. In addition, giving users instructions on how to initiate feedback themselves can reduce the perceived disruptiveness compared to asking users for feedback directly. Based on our findings, we discuss the implications and potential future directions for designing voice assistants to elicit user feedback for personalized voice experiences.

We report on an interview study with two groups, student volunteers (SV) and student volunteer chairs (SVC), to explore their experiences in contributing to an academic conference. We identified themes regarding their behaviors and perceptions when communicating with each other through an open coding approach. The analysis of the findings reveals that communication issues exist between SV and SVC. While SV faced challenges approaching SVC, SVC had experienced difficulties in finding the right SV to ask for assistance in the tasks. We also found that the information provided by SVC was not sufficient for SV to perform the assigned tasks. Similarly, SVC had a similar issue where they received limited information from former SVC. We present design implications that enable both SV and SVC to share their availability, preferences, and prior knowledge of potential tasks with each other. This is the first study that reports design opportunities to support SV and SVC.

In this article, we ask how well Australian households are matched to their neighbourhood social environments. We broadly replicate a previous study of matching and ask to what extent households live in communities that are similar in socio-economic status to their characteristics. And, when households move, do they relocate in such a way as to increase similarity to their neighbours? The processes are at the heart of understanding the urban structure, how it changes over time and the links to urban inequality. The article uses data on household incomes from the Household, Income and Labour Dynamic (HILDA) Survey to measure the degree of similarity between households and their neighbours. We study the variation in matching for the population as a whole, and by quintiles of median neighbourhood income. We also measure how individuals that change neighbourhoods increase their similarity to the destination neighbourhood. We find that with respect to matching there is considerable diversity in the levels of matching; and that with respect to residential change, households in general do not make major shifts to increase matching when we control for housing tenure and other household characteristics. There is a need for further replications to understand the nature of matching and the outcomes.

In this paper, the author explores some of the issues associated with teaching about compulsory heterosexuality and schooling in an undergraduate sociology programme. Using a novel approach to gathering data, the article analyses the stories students submitted about themselves or others who were counter normative in terms of gender and sexuality in school. Informed by the work of Ahmed and Foucault, this article explores what kinds of gendered and sexualised subject positions become possible through the stories of students, and how are these subject positions interpellated and constituted relationally? Despite progressive legislation, queer activism and the significant visibility of gender and sexuality counter-normative identities in the South African media, the analysis highlights that students’ position school attending queer youth as (1) stereotyped caricatured subjects, (2) objects of fear and (3) subjects of violence. These subject positions serve as straightening devices that interpellate queer school attending youth as unfamiliar, not belonging and unworthy and therefore requiring change. Insights from this article can inform the research and practice which is pivotal to addressing cisheteronormativity not only in schools but cultural ideas, norms and practices too.

This study examines the use of critical community-building—using dialogue as a collective to support, listen to, ask questions, and assist each other in thinking in critical ways—to support resettl...

How customers develop purchase intentions in online shopping has been an area of recent interest. In this study, we ask whether males and females leverage trust into and perceived reputation of online retailers differently in reporting purchase intentions. Drawing on the literature on differences in males and females in online shopping behaviors, we propose that females rely on reputation in developing purchase intentions whereas males rely on perceived trust in developing purchase intentions. In a sample of 727 respondents in Sweden, we find support for the proposed associations. Implications for online retailers are discussed.

In this article, we ask the question how individuals and the community share the burden of work tasks during prolonged co-creation processes. Building on theories of user community, co-crea...

Purpose The purpose of this paper is to compare online labor platforms (OLPs) such as Upwork, Fiverr, YoungOnes and Temper with traditional temp agencies. At a first glance, OLPs and temp agencies strongly resemble each other while they aim to meet the need for short-term labor of organizations. The authors ask the question how these labor market intermediaries differ on issues such as information technology usage, ways how labor supply and demand are matched and working conditions (e.g. status, pay and social security of workers). Design/methodology/approach Next to a review of the academic literature, the authors conducted interviews with representatives of six OLPs and temp agencies in the Netherlands as well as a legal specialist in Dutch labor law. Findings The authors found that OLPs and temp agencies differ on several issues. First, although OLPs rely on online marketplaces for matching labor supply and demand, temp agencies generally rely on human matchmakers. Second, although OLPs enable workers and client organizations to initiate transactions themselves, temp agencies employ representatives that do the matching for workers and clients. Third, and as a result, OLPs afford client organizations to almost instantly hire workers on-demand, whereas the flexibility and speed that temp agencies can offer depend on availability and processing capacity of human matchmakers. Originality/value According to the authors’ knowledge, this paper is the first to compare OLPs and temp agencies and, in doing so, offers academics and practitioners an analytical framework to compare different types of labor market intermediaries.

Given overall lack of gender diversity in the venture capital and entrepreneurship industry shown in Calder-Wang and Gompers (2017) we ask: What promotes greater gender diversity in hiring? Does diversity lead to better firm performance and higher investment returns? In this paper, using a unique dataset of the gender of venture capital partners’ children, we find strong evidence that when partners have more daughters, the propensity to hire female partners increases. Moreover, our instrumental variable results suggest that increased gender diversity improves deal and fund performance. Lastly, the effects are primarily driven by the gender of senior partners’ children.

Online shop companies that are currently running only use Microsoft excel in recording, selling, purchasing for inventory. In making invoices and purchases still use only notes. With this system running, there are many errors that often occur, such as the loss of sales invoices, the loss of travel documents and which result in no evidence of transactions that have occurred. Therefore we need a computerized system that can help to make sales purchases more easily and can check stock items very easily and accurately. The design of this system starts from the warehouse first to record incoming goods then make a purchase invoice and here the warehouse confirms to the shop owner, if approved, the owner will ask the admin to make stock adjustments, after the stock is reduced, the admin will confirm to the Warehouse and the Warehouse will make a travel document to be continued to the consumer.

In this contribution, I do not engage in digital disconnection merely as an empirical phenomenon but as a way of seeing digital culture and as a heuristic. I do not ask whether or not digital disconnection is possible, is good or bad, or should be advocated or overcome. Instead, I adopt Eva Illouz’s framework of a negative sociology of social bonds to explore what it would mean to study digital culture from the perspective of negative choice. The conceptual framework is illustrated with three empirical cases that show what it would mean to engage in a negative sociology of digital culture. The shift in perspective from positive bonds to the choice to disengage, not use, or exit certain fora makes visible how digital culture is not only increasingly characterized by polarization, but also how disconnection emerges as a civic virtue that puts the individual user’s responsibility at the forefront.

Purpose The intent of this tutorial is to radically shift engagement around the “types of questions” we ask around racism in communication sciences and disorders (CSD). We propose to move conversations away from diversity and inclusion and go deeper to look at the racist systems of oppression in higher education that have produced our predominantly White discipline. This low number of representations of racial minorities in CSD is extremely problematic and has deep, harmful, and far-reaching implications. The perpetuation of White production of knowledge and White culture harms minority students, faculty and clients, clinical service delivery, coursework content, and the research enterprise. Conclusions In this tutorial, we attempt to communicate the complexity of this issue as it relates to our profession and offer ideas that at least get the discussion started. In doing so, we (a) introduce the topic in the context of the history of racism in America and how White fragility makes this topic difficult to hear, (b) provide a problem statement specific to CSD, (c) introduce the concept of systems of oppression and how this concept can change how we face racism in CSD, and (d) provide future directions.

This paper studies the effect of the commonly used phrase “thanks in advance” on compliance with a small request. In a controlled laboratory experiment we ask participants to give a detailed answer to an open question. The treatment variable is whether or not they see the phrase “thanks in advance.” Our participants react to the treatment by exerting less effort in answering the request even though they perceive the phrase as polite.