The Nine Circles of Scientific Hell

Neuroskeptic,

doi:10.1177/1745691612459519

Cited by 57 publications

(21 citation statements)

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“…Our approach also draws attention to the tremendous analytical flexibility that is available in principle (Carp, 2012) , and to the all-too-common practice of keeping such explorations "behind the scenes" and only reporting the "best" strategy, leading to an inflation of positive findings reported in the literature (Neuroskeptic, 2012;Simonsohn, Nelson, & Simmons, 2014) . At a certain level, if all analyses conducted make sense (i.e., would pass a careful expert reviewer's scrutiny), they should all give a similar answer to the final question (conceptually equivalent to inter-rater reliability (Dubois & Adolphs, 2016) ).…”

Section: Summary Of Resultsmentioning

confidence: 99%

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Dubois

Galdi

Han

et al. 2017

Preprint

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Personality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging data from 884 young healthy adults in the Human Connectome Project (HCP) database. We attempted to predict personality traits from the "Big Five", as assessed with the NEO-FFI test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two inter-subject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; 3 denoising strategies; 2 alignment schemes; 3 models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=0.24, R 2 =0.024) almost as well as we could predict the score on a 24-item intelligence test (PMAT24_A_CR: r=0.26, R 2 =0.044). Other factors (Extraversion, Neuroticism, Agreeableness and Conscientiousness) yielded weaker predictions across results that were not statistically significant under permutation testing. We also derived two superordinate personality factors ("α" and "β") from a principal components analysis of the NEO-FFI factor scores, thereby reducing noise and enhancing the precision of these measures of personality. We could account for 5% of the variance in the β superordinate factor (r=0.27, R 2 =0.050), which loads highly on Openness to experience. We conclude with a discussion of the potential for predicting personality from neuroimaging data and make specific recommendations for the field.

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Section: Summary Of Resultsmentioning

confidence: 99%

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Dubois

Galdi

Han

et al. 2017

Preprint

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“…Culprits for the lack of replicability are small sample sizes [138], analytical flexibility [179] which fosters p-hacking [180] without appropriate control for the overall risk of false positives [181], and the bias to publish only statistically significant results (a.k.a. the file drawer problem [182]).…”

Section: Figurementioning

confidence: 99%

Building a Science of Individual Differences from fMRI

Dubois

Adolphs

2016

Trends in Cognitive Sciences

588

482

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To date, fMRI research has been concerned primarily with evincing generic principles of brain function through averaging data from multiple subjects. Given rapid developments in both hardware and analysis tools, the field is now poised to study fMRI-derived measures in individual subjects, and to relate these to psychological traits or genetic variations. We discuss issues of validity and reliability that arise when the focus shifts to individual subjects and that are widely applicable across imaging modalities. We also emphasize that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between-subject variability, sources of within-subject variability, and statistical power.

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“…very broad (e.g., Neuroskeptic, 2012), encompassing not only fraud but a whole array of flawed practices that differ in perniciousness. Although there are, obviously, things a researcher should never do, many other practices are not necessarily questionable because of what the researcher does (e.g., removing outliers, for which good reasons may exist) but because this information is not properly disclosed.…”

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confidence: 99%

The Transparency Paradox

Bernstein

2012

Administrative Science Quarterly

289

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Please do not quote or reference without citing the final publication (available at http://asq.sagepub.com):Bernstein, E. 2012 The Transparency Paradox: A Role for Privacy in Organizational Learning and Operational Control. Administrative Science Quarterly 57(2): 181-216. AbstractUsing data from embedded participant-observers and a field experiment at the second largest mobile phone factory in the world, located in China, I theorize and test the implications of transparent organizational design on workers' productivity and organizational performance. Drawing from theory and research on learning and control, I introduce the notion of a transparency paradox, whereby maintaining observability of workers may counterintuitively reduce their performance by inducing those being observed to conceal their activities through codes and other costly means; conversely, creating zones of privacy may, under certain conditions, increase performance. Empirical evidence from the field shows that even a modest increase in group-level privacy sustainably and significantly improves line performance, while qualitative evidence suggests that privacy is important in supporting productive deviance, localized experimentation, distraction avoidance, and continuous improvement. I discuss implications of these results for theory on learning and control and suggest directions for future research. information flows up the organization, as well as reduce the risk that localized problem solving will fail to contribute to organization-wide learning (Tucker, Edmondson, and Spear, 2002). Transparency concurrently may enable operational control by ensuring access to richer, more extensive, more accurate, more disaggregated, and more real-time data by managers and employees, thus improving both hierarchical control (Taylor, 1911;Adler and Borys, 1996; Sewell, 1998) and peer control (Barker, 1993). Senior leaders are therefore redesigning their organizations to make more work more visible more of the time, embracing innovations such as advancements in surveillance and knowledge search technologies (Sewell, 1998;Levinson, 2009), open workspace design (Zalesny and Farace, 1987), and "naked" communication of real-time data via advanced information technology tools (Tapscott and Ticoll, 2003). Keywords 2This trend toward transparency has been particularly evident in the design of the world's factories, where visual factory implementations have been "spreading . . . like a trail of gunpowder" (Greif, 1991: 1). Most modern-day facilities are designed to provide near-perfect observability of the actions and performance of every employee, line, and function. This observability serves as an important foundation for all aspects of the Toyota Production System DNA (Spear and Bowen, 1999) and is a necessary antecedent behind the seventh principle of the Toyota Way: "use visual control so no problems are hidden" (Liker, 2004: 149-158). Factory managers and employees need to see activity in order to improve it. Accurate observability also provides the basis for...

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The Nine Circles of Scientific Hell

Cited by 57 publications

References 0 publications

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Building a Science of Individual Differences from fMRI

The Transparency Paradox

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