Systems of (non-)diversity

The many tools that social and behavioral scientists use to gather data from their fellow humans have, in most cases, been honed on a rarefied subset of humanity: highly educated participants with unique capacities, experiences, motivations, and social expectations. Through this honing process, researchers have developed protocols that extract information from these participants with great efficiency. However, as researchers reach out to broader populations, it is unclear whether these highly refined protocols are robust to cultural differences in skills, motivations, and expected modes of social interaction. In this paper, we illustrate the kinds of mismatches that can arise when using these highly refined protocols with nontypical populations by describing our experience translating an apparently simple social discounting protocol to work in rural Bangladesh. Multiple rounds of piloting and revision revealed a number of tacit assumptions about how participants should perceive, understand, and respond to key elements of the protocol. These included facility with numbers, letters, abstract number lines, and 2D geometric shapes, and the treatment of decisions as a series of isolated events. Through onthe-ground observation and a collaborative refinement process, we developed a protocol that worked both in Bangladesh and among US college students. More systematic study of the process of adapting common protocols to new contexts will provide valuable information about the range of skills, motivations, and modes of interaction that participants bring to studies as we develop a more diverse and inclusive social and behavioral science. generalizability | diversity | cross-cultural | social discounting | Bangladesh I n 1932, the psychologist Rensis Likert (1) published his dissertation on a novel method for measuring attitudes. After giving university students printed statements about race relations, Likert asked them to check one of five options (strongly approve, approve, undecided, disapprove, and strongly disapprove) indicating how much they endorsed each of these statements. Likert then assigned numbers to these levels of approval and took an average across all statements. The simplicity of both the response format and construction of the scale soon spurred researchers to adopt elements of the technique to assess not only attitudes (Likert's original interest) but also subjective judgments along many dimensions, including likelihood, desirability, difficulty, and happiness (2). Today, after decades of testing and refinement on generations of participants, Likert's simple format has become a reliable mainstay of social and behavioral research.Given its ubiquity in the social and behavioral sciences, one might guess that a five-or seven-item Likert format is a natural way of asking humans about their subjective judgments. However, in the rare cases when researchers have described their experience using Likert items outside of formally educated populations, they have been met with mixed success (3,4). It turns out tha...

Section: Beyond the Likert Formatmentioning

confidence: 99%

Learning from failures of protocol in cross-cultural research

Hruschka

Munira

Jesmin

et al. 2018

“…However good the research, communicators must still consult with their external stakeholders. It is unrealistic to expect them to know how people very different from themselves view their world or the communicators (8,41,55). Even if those consultations only affirm what the research says, they are important as "speech acts."…”

Section: External Consultation: Are They Talking Effectively With Othermentioning

confidence: 99%

“…Each discipline owes its success to its tacit knowledge of how to work within its bounds. Those bounds can be so incommensurable that scientists from different disciplines struggle even to agree about how to disagree (7,8). Nonetheless, as argued by Communicating Science Effectively: A Research Agenda (1), the success of science communication depends on collaboration across disciplines.…”

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confidence: 99%

Evaluating science communication

Fischhoff

2018

Effective science communication requires assembling scientists with knowledge relevant to decision makers, translating that knowledge into useful terms, establishing trusted two-way communication channels, evaluating the process, and refining it as needed. Communicating Science Effectively: A Research Agenda [National Research Council (2017)] surveys the scientific foundations for accomplishing these tasks, the research agenda for improving them, and the essential collaborative relations with decision makers and communication professionals. Recognizing the complexity of the science, the decisions, and the communication processes, the report calls for a systems approach. This perspective offers an approach to creating such systems by adapting scientific methods to the practical constraints of science communication. It considers staffing (are the right people involved?), internal collaboration (are they talking to one another?), and external collaboration (are they talking to other stakeholders?). It focuses on contexts where the goal of science communication is helping people to make autonomous choices rather than promoting specific behaviors (e.g., voter turnout, vaccination rates, energy consumption). The approach is illustrated with research in two domains: decisions about preventing sexual assault and responding to pandemic disease.

“…The comparison of distant versus engaged perspectives is inevitably confounded with WEIRD versus non-WEIRD samples, vastly unequal previous investment in them, and (often implicit) default assumptions that derive from fields dominated by WEIRD researchers. The diversity of researchers and the researched is intertwined, and calls for increased diversity of scholars and scholarship (13,14) face research environments dominated by default (WEIRD) perspectives and values, including the perspective that objectivity requires distance. It is important to bear these factors in mind in considering how engagement may interact with risk factors and virtues in research.…”

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confidence: 99%

Should social scientists be distanced from or engaged with the people they study?

Nzinga

Rapp

Leatherwood

et al. 2018

Historical Background: Dominance of Default PopulationsHenrich et al.(3) noted that social and behavioral research overwhelmingly relies on WEIRD (Western, educated, industrialized, rich, and democratic) samples, samples that they argue are quite literally weird in that they are especially unrepresentative of the world at large. A "heat map" showing the locations of major research universities and who gets studied by them, we hypothesize, would reveal steep mountains and broad, flat plains as the primary contours. The underrepresented groups include communities that have traditionally been minoritized or This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, "Pressing Questions in the Study of Psychological and Behavioral Diversity," held September 7-9, 2017, at the Arnold and Mabel Beckman Center of the National Academies of Sciences and Engineering in Irvine, CA. The complete program and video recordings of most presentations are available on the NAS website at www.nasonline.org/ pressing-questions-in-diversity.