Samy Suissa
Jan 1, 2018; 41:6-10
Perspectives in Care

You could be forgiven for thinking the television images in the experiment were from 2006. They were really from 1982: Israeli forces were clashing with Arab militants in Lebanon. The world was watching, charges were flying, and the air was thick with grievance, hurt and outrage.

Antiwar liberals last week got to savor the four most satisfying words in the English language: "I told you so."

Long before word recently broke that white referees in the National Basketball Association were calling fouls at a higher rate on black athletes than on white athletes, and long before studies found racial disparities in how black and white applicants get called for job interviews, researchers no...

On Oct. 10, 2002, Hillary Rodham Clinton stood in the Senate to explain why she was authorizing President Bush to use force against Iraq: "In balancing the risks of action versus inaction, I think New Yorkers who have gone through the fires of hell may be more attuned to the risk of not acting. I...

Understand how customer brains work - these are the most important cognitive biases for e-commerce marketers.

The post 12 Cognitive Biases E-commerce Marketers Need to Know appeared first on Neuromarketing.

Our weekly round-up of the best psychology coverage from elsewhere on the web

Sex discrimination against women.

London : Stacy Bias, 2019.

Mikael Escobar-Bach, Yuri Goegebeur, Armelle Guillou.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1773--1795.

Abstract:
We consider bias-corrected estimation of the stable tail dependence function in the regression context. To this aim, we first estimate the bias of a smoothed estimator of the stable tail dependence function, and then we subtract it from the estimator. The weak convergence, as a stochastic process, of the resulting asymptotically unbiased estimator of the conditional stable tail dependence function, correctly normalized, is established under mild assumptions, the covariate argument being fixed. The finite sample behaviour of our asymptotically unbiased estimator is then illustrated on a simulation study and compared to two alternatives, which are not bias corrected. Finally, our methodology is applied to a dataset of air pollution measurements.

Yuling Yan, Bret Hanlon, Sebastien Roch, Karl Rohe.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1577--1610.

Abstract:
Respondent-driven sampling (RDS) collects a sample of individuals in a networked population by incentivizing the sampled individuals to refer their contacts into the sample. This iterative process is initialized from some seed node(s). Sometimes, this selection creates a large amount of seed bias. Other times, the seed bias is small. This paper gains a deeper understanding of this bias by characterizing its effect on the limiting distribution of various RDS estimators. Using classical tools and results from multi-type branching processes [12], we show that the seed bias is negligible for the Generalized Least Squares (GLS) estimator and non-negligible for both the inverse probability weighted and Volz-Heckathorn (VH) estimators. In particular, we show that (i) above a critical threshold, VH converge to a non-trivial mixture distribution, where the mixture component depends on the seed node, and the mixture distribution is possibly multi-modal. Moreover, (ii) GLS converges to a Gaussian distribution independent of the seed node, under a certain condition on the Markov process. Numerical experiments with both simulated data and empirical social networks suggest that these results appear to hold beyond the Markov conditions of the theorems.

Ran Dai, Hyebin Song, Rina Foygel Barber, Garvesh Raskutti.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 801--834.

Abstract:
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little is known about the bias. In this paper, we provide a sharp characterization, proving that the bias scales as $O(n^{-eta /3})$ up to log factors, where $1leq eta leq 2$ is the exponent corresponding to Hölder smoothness of the underlying mean. Importantly, this result only requires a strictly monotone mean and that the noise distribution has subexponential tails, without relying on symmetric noise or other restrictive assumptions.

Christopher Withers, Saralees Nadarajah

Source: Electron. J. Statist., Volume 4, 1--14.

Abstract:
We consider M estimation of a regression model with a nuisance parameter and a vector of other parameters. The unknown distribution of the residuals is not assumed to be normal or symmetric. Simple and easily estimated formulas are given for the dominant terms of the bias and skewness of the parameter estimates. For the linear model these are proportional to the skewness of the ‘independent’ variables. For a nonlinear model, its linear component plays the role of these independent variables, and a second term must be added proportional to the covariance of its linear and quadratic components. For the least squares estimate with normal errors this term was derived by Box [1]. We also consider the effect of a large number of parameters, and the case of random independent variables.

Feature screening is a powerful tool in processing high-dimensional data. When the sample size N and the number of features p are both large, the implementation of classic screening methods can be numerically challenging. In this paper, we propose a distributed screening framework for big data setup. In the spirit of 'divide-and-conquer', the proposed framework expresses a correlation measure as a function of several component parameters, each of which can be distributively estimated using a natural U-statistic from data segments. With the component estimates aggregated, we obtain a final correlation estimate that can be readily used for screening features. This framework enables distributed storage and parallel computing and thus is computationally attractive. Due to the unbiased distributive estimation of the component parameters, the final aggregated estimate achieves a high accuracy that is insensitive to the number of data segments m. Under mild conditions, we show that the aggregated correlation estimator is as efficient as the centralized estimator in terms of the probability convergence bound and the mean squared error rate; the corresponding screening procedure enjoys sure screening property for a wide range of correlation measures. The promising performances of the new method are supported by extensive numerical examples.

Vinod Venkatraman
Mar 9, 2011; 31:3712-3718
BehavioralSystemsCognitive

Gregor Thut
Sep 13, 2006; 26:9494-9502
BehavioralSystemsCognitive

Biases in sensory perception can arise from both experimental manipulations and personal trait-like features. These idiosyncratic biases and their neural underpinnings are often overlooked in studies on the physiology underlying perception. A potential candidate mechanism reflecting such idiosyncratic biases could be spontaneous alpha band activity, a prominent brain rhythm known to influence perceptual reports in general. Using a temporal order judgment task, we here tested the hypothesis that alpha power reflects the overcoming of an idiosyncratic bias. Importantly, to understand the interplay between idiosyncratic biases and contextual (temporary) biases induced by experimental manipulations, we quantified this relation before and after temporal recalibration. Using EEG recordings in human participants (male and female), we find that prestimulus frontal alpha power correlates with the tendency to respond relative to an own idiosyncratic bias, with stronger α leading to responses matching the bias. In contrast, alpha power does not predict response correctness. These results also hold after temporal recalibration and are specific to the alpha band, suggesting that alpha band activity reflects, directly or indirectly, processes that help to overcome an individual's momentary bias in perception. We propose that combined with established roles of parietal α in the encoding of sensory information frontal α reflects complementary mechanisms influencing perceptual decisions.

SIGNIFICANCE STATEMENT The brain is a biased organ, frequently generating systematically distorted percepts of the world, leading each of us to evolve in our own subjective reality. However, such biases are often overlooked or considered noise when studying the neural mechanisms underlying perception. We show that spontaneous alpha band activity predicts the degree of biasedness of human choices in a time perception task, suggesting that alpha activity indexes processes needed to overcome an individual's idiosyncratic bias. This result provides a window onto the neural underpinnings of subjective perception, and offers the possibility to quantify or manipulate such priors in future studies.

Bank of England Working Papers by Nicola Garbarino and Benjamin Guin

As expected, the Education Department has delayed a rule that would require states to take a standardized approach in evaluating districts for minority bias in special education.

Education Week's top English-language learner stories on 2019 explored who's teaching the nation's English-learners and the struggles those educators encounter on the job, how the Trump administration's immigration policies affected students and their families and examined why more schools in the Un

Although several randomized trials have examined the efficacy of serotonin receptor inhibitors in the treatment of repetitive behaviors, there still remains clinical uncertainty as to whether these agents are effective in treating such behaviors in children and adults with autism spectrum disorders.

The goal of this meta-analysis was to examine randomized trials of serotonin receptor inhibitors for treating repetitive behaviors in autism spectrum disorders. Although a small but significant effect of these agents was observed, this effect is likely due to the selective publication of trial results. (Read the full article)

The rule requires states to use a standard method in determining if districts are biased in how they identify minority students, discipline them, or place them in restrictive settings.

Even the best intentioned educators often harbor blind spots, write Re-Imagining Migration's Adam Strom and Veronica Boix Mansilla.

Education Week's top English-language learner stories on 2019 explored who's teaching the nation's English-learners and the struggles those educators encounter on the job, how the Trump administration's immigration policies affected students and their families and examined why more schools in the Un

Children adapt their attitudes toward reading to conform to their classmates' perceived gender stereotypes, in ways that put boys at a disadvantage, according to a new study in the journal Child Development.

Deep-learning algorithms suffer from a fundamental problem: They can adopt unwanted biases from the data on which they're trained. In healthcare, this can lead to bad diagnoses and care recommendations.

California's proposed curriculum guide in ethnic studies is being sent back for substantial revision after a pileup of criticism that it's anti-Semitic.

Students of color don't need to get "grittier," writes New America's Jenny Muñiz. They need us to fix institutional racism.

A study by RTI International and Johns Hopkins University found evidence that teachers' assumptions and biases about their students' families can change after visiting their homes.

ESPN's team of college sports writers breaks down the best individual performances they've seen in their collective decades around sports.

While AI has unquestionably led to some massively significant technological breakthroughs for consumers and businesses alike, it's also got a darker side that can lead to major issues. The public use of citizen data to feed algorithms and things li...

There is absolutely no doubt that artificial intelligence has already driven — and will continue to drive — some of the world's most fascinating and advanced technological achievements. While AI and ML continues to permeate lives of end...

Macrophages in the lung detect and respond to influenza A virus (IAV), determining the nature of the immune response. Using terminal-depth cap analysis of gene expression (CAGE), we quantified transcriptional activity of both host and pathogen over a 24-h time course of IAV infection in primary human monocyte-derived macrophages (MDMs). This method allowed us to observe heterogenous host sequences incorporated into IAV mRNA, "snatched" 5' RNA caps, and corresponding RNA sequences from host RNAs. In order to determine whether cap-snatching is random or exhibits a bias, we systematically compared host sequences incorporated into viral mRNA ("snatched") against a complete survey of all background host RNA in the same cells, at the same time. Using a computational strategy designed to eliminate sources of bias due to read length, sequencing depth, and multimapping, we were able to quantify overrepresentation of host RNA features among the sequences that were snatched by IAV. We demonstrate biased snatching of numerous host RNAs, particularly small nuclear RNAs (snRNAs), and avoidance of host transcripts encoding host ribosomal proteins, which are required by IAV for replication. We then used a systems approach to describe the transcriptional landscape of the host response to IAV, observing many new features, including a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation, seen in response to other treatments.

IMPORTANCE Infection with influenza A virus (IAV) infection is responsible for an estimated 500,000 deaths and up to 5 million cases of severe respiratory illness each year. In this study, we looked at human primary immune cells (macrophages) infected with IAV. Our method allows us to look at both the host and the virus in parallel. We used these data to explore a process known as "cap-snatching," where IAV snatches a short nucleotide sequence from capped host RNA. This process was believed to be random. We demonstrate biased snatching of numerous host RNAs, including those associated with snRNA transcription, and avoidance of host transcripts encoding host ribosomal proteins, which are required by IAV for replication. We then describe the transcriptional landscape of the host response to IAV, observing new features, including a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation, seen in response to other treatments.

Glial cell line–derived neurotrophic factor (GDNF) is a growth factor that regulates the health and function of neurons and other cells. GDNF binds to GDNF family receptor α1 (GFRa1), and the resulting complex activates the RET receptor tyrosine kinase and subsequent downstream signals. This feature restricts GDNF activity to systems in which GFRa1 and RET are both present, a scenario that may constrain GDNF breadth of action. Furthermore, this co-dependence precludes the use of GDNF as a tool to study a putative functional cross-talk between GFRa1 and RET. Here, using biochemical techniques, terminal deoxynucleotidyl transferase dUTP nick end labeling staining, and immunohistochemistry in murine cells, tissues, or retinal organotypic cultures, we report that a naphthoquinone/quinolinedione family of small molecules (Q compounds) acts as RET agonists. We found that, like GDNF, signaling through the parental compound Q121 is GFRa1-dependent. Structural modifications of Q121 generated analogs that activated RET irrespective of GFRa1 expression. We used these analogs to examine RET–GFRa1 interactions and show that GFRa1 can influence RET-mediated signaling and enhance or diminish AKT Ser/Thr kinase or extracellular signal-regulated kinase signaling in a biased manner. In a genetic mutant model of retinitis pigmentosa, a lead compound, Q525, afforded sustained RET activation and prevented photoreceptor neuron loss in the retina. This work uncovers key components of the dynamic relationships between RET and its GFRa co-receptor and provides RET agonist scaffolds for drug development.

'The Real Michael Jackson' aired on BBC2 in March

California state agencies argue that women who worked at the video game company could deserve up to $400 million. The company—and the lawyers for women who worked there—strongly disagree.

Despite more relaxed coronavirus restrictions in South Australia and Western Australia, the AFL says it does not want clubs from those states training in bigger groups until Victorian teams are allowed to do so.

A Fairfield, Calif., couple was indicted today by a federal grand jury in Sacramento, Calif., on federal civil rights charges related to an alleged bias-motivated assault on an Indian-American couple. The two-count indictment alleges that on the evening of July 14, 2007, Joseph and Georgia Silva committed a bias-motivated assault on another couple at a public beach in South Lake Tahoe, Calif.

Today, the Department of Justice issued a letter of findings describing problems in the Missoula County, Mont., Attorney’s Office’s response to sexual assault, and concluding that there is substantial evidence that the County Attorney’s response to sexual assault discriminates against women.

Noting that African-American and Hispanic males are arrested at disproportionately high rates, U.S. Attorney General Eric Holder said Monday that the Justice Department will seek to collect data about stops, searches and arrests as part of a larger effort to analyze and reduce the possible effect of bias within the criminal justice system.

How algorithms designed to alleviate poverty can perpetuate it instead

Most Americans are currently under a stay-at-home order to mitigate the spread of the novel coronavirus, or COVID-19. But in a matter of days and weeks, some U.S. governors will decide if residents can return to their workplaces, churches, beaches, commercial shopping centers, and other areas deemed non-essential over the last few months. Re-opening states…

The NCAA basketball tournament is one of the most-viewed sporting events in the United States. In 2019, nearly 20 million viewers watched the championship game, and each tournament game (67 total) averaged about 10 million viewers. Over 17 million people completed a March Madness tournament bracket for the 68-team tournament. Among youth, basketball is one…

In the futuristic 2002 film “Minority Report,” law enforcement uses a predictive technology that includes artificial intelligence (AI) for risk assessments to arrest possible murderers before they commit crimes. However, a police officer is now one of the accused future murderers and is on the run from the Department of Justice to prove that the…

It is not news that, for all its promised benefits, artificial intelligence has a bias problem. Concerns regarding racial or gender bias in AI have arisen in applications as varied as hiring, policing, judicial sentencing, and financial services. If this extraordinary technology is going to reach its full potential, addressing bias will need to be…