Varieties of social cognition

Recent actions. KEYWORDS: implicit social work Influence within cognition, unconsciousness psychology demonstrates is cognition, corroborated that implicit unconscious by strong measures, empirical cognition priming, evidence, plays automaticity, a but central unconscious consciousness role in the states judgments are difficult and actions to verify. of We individuals. discuss procedures We distinguish aimed between at providing two basic conclusive types evidence unconscious of state social unconsciousness, cognition: unconsciousness and apply them of the to influences recent empirical on judgments findings. and actions, and unconscious of the mental states (i.e., attitudes and feelings) that give rise to judgments After reading words related to stereotypes of the elderly, such as “Florida ” and “wrinkle, ” people tend to walk more slowly (Bargh, Chen, & Burrows, 1996). Being subliminally exposed to pictures of African American males makes people hostile, and thinking about professors improves their performance at Trivial Pursuit (Bargh et al., 1996; Dijksterhuis & van Knippenberg, 1998). People are more likely to mistakenly judge a male to be famous, and an African American to be a criminal (Banaji & Bhaskar, 2000; Banaji & Greenwald, 1995; Payne, 2001). Based on these and other similarly dramatic findings, we and many other psychologists have come to agree with Bargh and Chartrand (1999), who proposed that: “... most of a person’s everyday life is determined not by their conscious intentions and deliberate choices but by mental processes that are put into motion by features of the environment and that operate outside of conscious awarenes

Same data, different conclusions:Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

The motivated use of moral principles

Abstract Five studies demonstrated that people selectively use general moral principles to rationalize preferred moral conclusions. In Studies 1a and 1b, college students and community respondents were presented with variations on a traditional moral scenario that asked whether it was permissible to sacrifice one innocent man in order to save a greater number of people. Political liberals, but not relatively more conservative participants, were more likely to endorse consequentialism when the victim had a stereotypically White American name than when the victim had a stereotypically Black American name. Study 2 found evidence suggesting participants believe that the moral principles they are endorsing are general in nature: when presented sequentially with both versions of the scenario, liberals again showed a bias in their judgments to the initial scenario, but demonstrated consistency thereafter. Study 3 found conservatives were more likely to endorse the unintended killing of innocent civilians when Iraqis civilians were killed than when Americans civilians were killed, while liberals showed no significant effect. In Study 4, participants primed with patriotism were more likely to endorse consequentialism when Iraqi civilians were killed by American forces than were participants primed with multiculturalism. However, this was not the case when American civilians were killed by Iraqi forces. Implications for the role of reason in moral judgment are discussed

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples.publishedVersio

Scientific Utopia III: crowdsourcing science

Most scientific research is conducted by small teams of investigators who together formulate hypotheses, collect data, conduct analyses, and report novel findings. These teams operate independently as vertically integrated silos. Here we argue that scientific research that is horizontally distributed can provide substantial complementary value, aiming to maximize available resources, promote inclusiveness and transparency, and increase rigor and reliability. This alternative approach enables researchers to tackle ambitious projects that would not be possible under the standard model. Crowdsourced scientific initiatives vary in the degree of communication between project members from largely independent work curated by a coordination team to crowd collaboration on shared activities. The potential benefits and challenges of large-scale collaboration span the entire research process: ideation, study design, data collection, data analysis, reporting, and peer review. Complementing traditional small science with crowdsourced approaches can accelerate the progress of science and improve the quality of scientific research

Getting Explicit about the Implicit: A Taxonomy of Implicit Measures and Guide for their Use in Organizational Research

Accumulated evidence from social and cognitive psychology suggests that many behaviors are driven by processes operating outside of awareness, and an array of implicit measures to capture such processes have been developed. Despite their potential application, implicit measures have received relatively modest attention within the organizational sciences, due in part to barriers to entry and uncertainty about appropriate use of available measures. The current paper is intended to serve as an implicit measurement “toolkit” for organizational scholars, and as such our goals are fourfold. First, we present theory critical to implicit measures, highlighting advantages of capturing implicit processes in organizational research. Second, we present a functional taxonomy of implicit measures (i.e., accessibility-based, association-based, and interpretation-based measures) and explicate assumptions and appropriate use of each. Third, we discuss key criteria to help researchers identify specific implicit measures most appropriate for their own work, including a discussion of principles for the psychometric validation of implicit measures. Fourth, we conclude by identifying avenues for impactful “next generation” research within the organizational sciences that would benefit from the use of implicit measures.Keywords: Indirect measures, Implicit measures, Nonconscious processes, Automaticit

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples.</p

A creative destruction approach to replication: Implicit work and sex morality across cultures

How can we maximize what is learned from a replication study? In the creative destruction approach to replication, the original hypothesis is compared not only to the null hypothesis, but also to predictions derived from multiple alternative theoretical accounts of the phenomenon. To this end, new populations and measures are included in the design in addition to the original ones, to help determine which theory best accounts for the results across multiple key outcomes and contexts. The present pre-registered empirical project compared the Implicit Puritanism account of intuitive work and sex morality to theories positing regional, religious, and social class differences; explicit rather than implicit cultural differences in values; self-expression vs. survival values as a key cultural fault line; the general moralization of work; and false positive effects. Contradicting Implicit Puritanism's core theoretical claim of a distinct American work morality, a number of targeted findings replicated across multiple comparison cultures, whereas several failed to replicate in all samples and were identified as likely false positives. No support emerged for theories predicting regional variability and specific individual-differences moderators (religious affiliation, religiosity, and education level). Overall, the results provide evidence that work is intuitively moralized across cultures

Consensus-based guidance for conducting and reporting multi-analyst studies

International audienceAny large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science