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Concern over social scientists' inability to reproduce empirical research has spawned a vast and rapidly growing literature. The size and growth of this literature make it difficult for newly interested academics to come up to speed. Here, we provide a formal text modeling approach to characterize the entirety of the field, which allows us to summarize the breadth of this literature and identify core themes. We construct and analyze text networks built from 1,947 articles to reveal differences across social science disciplines within the body of reproducibility publications and to discuss the diversity of subtopics addressed in the literature. This field-wide view suggests that reproducibility is a heterogeneous problem with multiple sources for errors and strategies for solutions, a finding that is somewhat at odds with calls for largely passive remedies reliant on open science. We propose an alternative rigor and reproducibility model that takes an active approach to rigor prior to publication, which may overcome some of the shortfalls of the postpublication model. [ABSTRACT FROM AUTHOR]

Presents a study based on data from the National Organizations Study of the relationships between indicators of high-performance work organizations and measures of organizational performance. Characteristics of high-performing work organizations; Impact of human resource policies and practices on organizational performance.

Background: Physicians do not prescribe opioid analgesics for pain treatment equally across groups, and such disparities may pose significant public health concerns. Although research suggests that institutional constraints and cultural stereotypes influence doctors' treatment of pain, prior quantitative evidence is mixed. The objective of this secondary analysis is therefore to clarify which institutional constraints and patient demographics bias provider prescribing of opioid analgesics.Methods: We used electronic medical record data from an emergency department of a large U.S hospital during years 2008-2014. We ran multi-level logistic regression models to estimate factors associated with providing an opioid prescription during a given visit while controlling for ICD-9 diagnosis codes and between-patient heterogeneity.Results: A total of 180,829 patient visits for 63,513 unique patients were recorded during the period of analysis. Overall, providers were significantly less likely to prescribe opioids to the same individual patient when the visit occurred during higher rates of emergency department crowding, later times of day, earlier in the week, later years in our sample, and when the patient had received fewer previous opioid prescriptions. Across all patients, providers were significantly more likely to prescribe opioids to patients who were middle-aged, white, and married. We found no bias towards women and no interaction effects between race and crowding or between race and sex.Conclusions: Providers tend to prescribe fewer opioids during constrained diagnostic situations and undertreat pain for patients from high-risk and marginalized demographic groups. Potential harms resulting from previous treatment decisions may accumulate by informing future treatment decisions. [ABSTRACT FROM AUTHOR]