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

Negotiation Impasses: Types, Causes, and Resolutions

Although impasses are frequently experienced by negotiators, are featured in newspaper articles, and are reflected in online searches and can be costly, negotiation scholarship does not appear to consider them seriously as phenomena worth explaining. A review of negotiation tasks to study impasses reveals that they bias negotiators toward agreement. We systematically organize past findings on impasses and integrate them in the impasse type, cause, and resolution model (ITCR model). Our fundamental assumption is that a positive bargaining zone does not imply symmetric preferences for an agreement. One or both negotiators may prefer an impasse over an agreement despite a positive bargaining zone. We argue that it is beneficial for management research to distinguish between three impasse types: If both negotiators perceive benefit from an impasse, they are wanted; if one negotiator perceives benefits from an impasse, they are forced; and if both do not perceive benefits from the impasse, they are unwanted. We review structural (e.g., bargaining zone, communication channels), interpersonal (e.g., tough tactics, emotions), and intrapersonal (e.g., biases, available information, and framing) factors as the likely antecedents of the three impasse types. We also examine evidence that suggests that wanted impasses can be resolved by changing the negotiation structure for both parties, forced impasses can be resolved through persuasion, and unwanted impasses can be overcome by debiasing both parties. Finally, we review current methodological guidance and provide updated recommendations on how scholars should deal with impasses in both study designs and data analyses

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

Selective interactions of boundaries with upstream region of Abd-B promoter in Drosophila bithorax complex and role of dCTCF in this process

Expression of the genes Ubx, abd-A, and Abd-B of the bithorax complex depends on its cis-regulatory region, which is divided into discrete functional domains (iab). Boundary/insulator elements, named Mcp, Fab-6, Fab-7 and Fab-8 (PTS/F8), have been identified at the borders of the iab domains. Recently, binding sites for a Drosophila homolog of the vertebrate insulator protein CTCF have been identified in Mcp, Fab-6 and Fab-8 and also in several regions that correspond to predicted boundaries, Fab-3 and Fab-4 in particular. Taking into account the inability of the yeast GAL4 activator to stimulate the white promoter when the activator and the promoter are separated by a 5-kb yellow gene, we have tested functional interactions between the boundaries. The results show that all dCTCF-containing boundaries interact with each other. However, inactivation of dCTCF binding sites in Mcp, Fab-6 and PTS/F8 only partially reduces their ability to interact, suggesting the presence of additional protein(s) supporting distant interactions between the boundaries. Interestingly, only Fab-6, Fab-7 (which contains no dCTCF binding sites) and PTS/F8 interact with the upstream region of the Abd-B promoter. Thus, the boundaries might be involved in supporting the specific interactions between iab enhancers and promoters of the bithorax complex