Antiracist Curriculum and Digital Platforms: Evidence from Black Lives Matter

In this paper, we examine the impact of racially charged events on the demand for antiracist classroom resources in U.S. public schools. We use book requests made by teachers on DonorsChoose, the largest crowdfunding platform for public school teachers, as a measure of intent to address race-related topics in the classroom. We use the precise timing of high-profile police brutality and other racially charged events in the United States (2010–2020) to identify their effect on antiracism requests relative to a control group. We find a significant increase in antiracism requests following the killing of George Floyd in 2020 and a null effect for all other events in the decade. We also find an increase in requests for books featuring Latinx, Asian, Muslim, and Jewish cultures, suggesting that a focus on equality for one group can spill over and yield culturally aware dialogues for other groups as well. Event studies suggest that local protests played a role in motivating some of the teachers to post these requests. In just four months following George Floyd’s death, $3.4 million worth of books featuring authors and characters from marginalized communities were successfully funded, reaching more than half a million students. Text analysis of impact notes posted by teachers suggests that hundreds of thousands of young students are being engaged in discussions about positive affirmation and cross-cultural acceptance. This paper was accepted by D.J. Wu, information systems.

Providing Evidence for the Null Hypothesis in Functional Magnetic Resonance Imaging Using Group-Level Bayesian Inference

Classical null hypothesis significance testing is limited to the rejection of the point-null hypothesis; it does not allow the interpretation of non-significant results. This leads to a bias against the null hypothesis. Herein, we discuss statistical approaches to ‘null effect’ assessment focusing on the Bayesian parameter inference (BPI). Although Bayesian methods have been theoretically elaborated and implemented in common neuroimaging software packages, they are not widely used for ‘null effect’ assessment. BPI considers the posterior probability of finding the effect within or outside the region of practical equivalence to the null value. It can be used to find both ‘activated/deactivated’ and ‘not activated’ voxels or to indicate that the obtained data are not sufficient using a single decision rule. It also allows to evaluate the data as the sample size increases and decide to stop the experiment if the obtained data are sufficient to make a confident inference. To demonstrate the advantages of using BPI for fMRI data group analysis, we compare it with classical null hypothesis significance testing on empirical data. We also use simulated data to show how BPI performs under different effect sizes, noise levels, noise distributions and sample sizes. Finally, we consider the problem of defining the region of practical equivalence for BPI and discuss possible applications of BPI in fMRI studies. To facilitate ‘null effect’ assessment for fMRI practitioners, we provide Statistical Parametric Mapping 12 based toolbox for Bayesian inference.

In for a penny, in for a pound: examining motivated memory through the lens of retrieved context models

When people encounter items that they believe will help them gain reward, they later remember them better than others. A recent model of emotional memory, the emotional context maintenance and retrieval model (eCMR), predicts that these effects would be stronger when stimuli that predict high and low reward can compete with each other during both encoding and retrieval. We tested this prediction in two experiments. Participants were promised £1 for remembering some pictures, but only a few pence for remembering others. Their recall of the content of the pictures they saw was tested after 1 min and, in experiment 2, also after 24 h. Memory at the immediate test showed effects of list composition. Recall of stimuli that predicted high reward was greater than of stimuli that predicted lower reward, but only when high- and low-reward items were studied and recalled together, not when they were studied and recalled separately. More high-reward items in mixed lists were forgotten over a 24-h retention interval compared with items studied in other conditions, but reward did not modulate the forgetting rate, a null effect that should be replicated in a larger sample. These results confirm eCMR's predictions, although further research is required to compare that model against alternatives.

The Diversity Gap: When Diversity Matters for Knowledge

Can diversity make for better science? Although diversity has ethical and political value, arguments for its epistemic value require a bridge between normative and mechanistic considerations, demonstrating why and how diversity benefits collective intelligence. However, a major hurdle is that the benefits themselves are rather mixed: Quantitative evidence from psychology and behavioral sciences sometimes shows a positive epistemic effect of diversity, but often shows a null effect, or even a negative effect. Here we argue that to make progress with these why and how questions, we need first to rethink when one ought to expect a benefit of cognitive diversity. In doing so, we highlight that the benefits of cognitive diversity are not equally distributed about collective intelligence tasks and are best seen for complex, multistage, creative problem solving, during problem posing and hypothesis generation. Throughout, we additionally outline a series of mechanisms relating diversity and problem complexity, and show how this perspective can inform metascience questions.

Improved Estimation of Phenotypic Correlations Using Summary Association Statistics

Estimating the phenotypic correlations between complex traits and diseases based on their genome-wide association summary statistics has been a useful technique in genetic epidemiology and statistical genetics inference. Two state-of-the-art strategies, Z-score correlation across null-effect single nucleotide polymorphisms (SNPs) and LD score regression intercept, were widely applied to estimate phenotypic correlations. Here, we propose an improved Z-score correlation strategy based on SNPs with low minor allele frequencies (MAFs), and show how this simple strategy can correct the bias generated by the current methods. The low MAF estimator improves phenotypic correlation estimation, thus it is beneficial for methods and applications using phenotypic correlations inferred from summary association statistics.

The Three E’s of Private Tuition in India: Expansion, Expenditure, and Effect

Private tuition (PT) is a common phenomenon in India. Today, it is a multi-billion U.S. dollar (USD) market and the third major contributor of household expenses in India. However, “the effect of PT on academic achievement of the students” is a subjective statement and is being questioned by its very outcomes. Literature reveals that PT has neither a “positive” nor a “null” effect on an individual’s learning. However, assertively, we can conclude that PT comes with a baggage of “toxic by-products” for mainstream education. It necessitates implementing a regulatory mechanism for PT. Nevertheless, institutions need to extend additional support.

Acute alcohol intoxication and the cocktail party problem: do “mocktails” help or hinder?

Rationale To test the notion that alcohol impairs auditory attentional control by reducing the listener’s cognitive capacity. Objectives We examined the effect of alcohol consumption and working memory span on dichotic speech shadowing and the cocktail party effect—the ability to focus on one of many simultaneous speakers yet still detect mention of one’s name amidst the background speech. Alcohol was expected either to increase name detection, by weakening the inhibition of irrelevant speech, or reduce name detection, by restricting auditory attention on to the primary input channel. Low-span participants were expected to show larger drug impairments than high-span counterparts. Methods On completion of the working memory span task, participants (n = 81) were randomly assigned to an alcohol or placebo beverage treatment. After alcohol absorption, they shadowed speech presented to one ear while ignoring the synchronised speech of a different speaker presented to the other. Each participant’s first name was covertly embedded in to-be-ignored speech. Results The “cocktail party effect” was not affected by alcohol or working memory span, though low-span participants made more shadowing errors and recalled fewer words from the primary channel than high-span counterparts. Bayes factors support a null effect of alcohol on the cocktail party phenomenon, on shadowing errors and on memory for either shadowed or ignored speech. Conclusion Findings suggest that an alcoholic beverage producing a moderate level of intoxication (M BAC ≈ 0.08%) neither enhances nor impairs the cocktail party effect.