Phonology as the source of syllable frequency effects in visual word recognition: Evidence from French

In order to investigate whether syllable frequency effects in visual word recognition can be attributed to phonologically or orthographically defined syllables, we designed one experiment that allowed six critical comparisons. Whereas only a weak effect was obtained when both orthographic and phonological syllable frequency were conjointly manipulated in Comparison 1, robust effects for phonological and null effects for orthographic syllable frequency were found in Comparisons 2 and 3. Comparisons 4 and 5 showed that the syllable frequency effect does not result from a confound with the frequency of letter or phoneme clusters at the beginning of words. The syllable frequency effect was shown to diminish with increasing word frequency in Comparison 6. These results suggest that visually presented polysyllabic words are parsed into phonologically defined syllables during visual word recognition. Materials and links may be accessed at www.psychonomic.org/archive.     

PyEPL: A cross-platform experiment-programming library

PyEPL (the Python Experiment-Programming Library) is a Python library which allows cross-platform and object-oriented coding of behavioral experiments. It provides functions for displaying text and images onscreen, as well as playing and recording sound, and is capable of rendering 3-D virtual environments forspatial-navigation tasks. It is currently tested for Mac OS X and Linux. It interfaces with Activewire USB cards (on Mac OS X) and the parallel port (on Linux) for synchronization of experimental events with physiological recordings. In this article, we first present two sample programs which illustrate core PyEPL features. The examples demonstrate visual stimulus presentation, keyboard input, and simulation and exploration of a simple 3-D environment. We then describe the components and strategies used in implementing PyEPL.     

Choosing the best method for local validity estimation: relative accuracy of meta-analysis versus a local study versus Bayes-analysis

This study assessed the relative accuracy of 3 techniques--local validity studies, meta-analysis, and Bayesian analysis--for estimating test validity, incremental validity, and adverse impact in the local selection context. Bayes-analysis involves combining a local study with nonlocal (meta-analytic) validity data. Using tests of cognitive ability and personality (conscientiousness) as predictors, an empirically driven selection scenario illustrates conditions in which each of the 3 estimation techniques performs best. General recommendations are offered for how to estimate local parameters, based on true population variability and the number of studies in the meta-analytic prior. Benefits of empirical Bayesian analysis for personnel selection are demonstrated, and equations are derived to help guide the choice of a local validity technique (i.e., meta-analysis vs. local study vs. Bayes-analysis).     

Visual and phonological codes in letter and word recognition: Evidence from incremental priming

Critical issues in letter and word priming were investigated using the novel incremental priming technique . This technique adds a parametric manipulation of prime duration (or prime intensity) to the traditional design of a fast masked priming study. By doing so, additional information on the time course and nature of priming effects can be obtained. In Experiment 1, cross-case letter priming (a-A) was investigated in both alphabetic decision (letter/non-letter classification) and letter naming. In Experiment 2, cross-case word priming was investigated in lexical decision and naming. Whereas letter priming in alphabetic decision was most strongly determined by visual overlap between prime and target, word priming in lexical decision was facilitated by both orthographic and phonological information. Orthographic activation was stronger and occurred earlier than phonological activation. In letter and word naming, in contrast, priming effects were most strongly determined by phonological/articulatory information. Differences and similarities between letter and word recognition are discussed in the light of the incremental priming data.     

Avoid violence,rioting, and outrage; approach celebration,delight, and strength: Using large text corpora to compute valence,arousal, and the basic emotions

Ever since Aristotle discussed the issue in Book II of his Rhetoric, humans have attempted to identify a set of “basic emotion labels”. In this paper we propose an algorithmic method for evaluating sets of basic emotion labels that relies upon computed co-occurrence distances between words in a 12.7-billion-word corpus of unselected text from USENET discussion groups. Our method uses the relationship between human arousal and valence ratings collected for a large list of words, and the co-occurrence similarity between each word and emotion labels. We assess how well the words in each of 12 emotion label sets—proposed by various researchers over the past 118 years—predict the arousal and valence ratings on a test and validation dataset, each consisting of over 5970 items. We also assess how well these emotion labels predict lexical decision residuals (LDRTs), after co-varying out the effects attributable to basic lexical predictors. We then demonstrate a generalization of our method to determine the most predictive “basic” emotion labels from among all of the putative models of basic emotion that we considered. As well as contributing empirical data towards the development of a more rigorous definition of basic emotions, our method makes it possible to derive principled computational estimates of emotionality—specifically, of arousal and valence—for all words in the language.     

How Discrimination Impacts Sociopolitical Behavior: A Multidimensional Perspective

The conventional wisdom regarding the impact of discrimination on political behavior is that the perception of prejudiced treatment motivates individuals to take political action. This study challenges this common conception by demonstrating that the source of discrimination can play a significant role in whether perceived or experienced injustice leads to activism or withdrawal from sociopolitical life. Drawing from political science and social psychology literature, this study provides a new perspective on the potential effects of discrimination on a relatively new marginalized group in the United States. Specifically, an important distinction is drawn between political (systematic) and societal (interpersonal) discrimination in analyzing the sociopolitical behavior of American Muslims in the aftermath of the 9/11 terrorist attacks. The results will hopefully encourage scholars to take a deeper look at the nexus between discrimination and democratic engagement, which is an important, complex, multidimensional, and understudied topic.     

The evolutionary basis of risky adolescent behavior: implications for science, policy, and practice

This article proposes an evolutionary model of risky behavior in adolescence and contrasts it with the prevailing developmental psychopathology model. The evolutionary model contends that understanding the evolutionary functions of adolescence is critical to explaining why adolescents engage in risky behavior and that successful intervention depends on working with, instead of against, adolescent goals and motivations. The current article articulates 5 key evolutionary insights into risky adolescent behavior: (a) The adolescent transition is an inflection point in development of social status and reproductive trajectories; (b) interventions need to address the adaptive functions of risky and aggressive behaviors like bullying; (c) risky adolescent behavior adaptively calibrates over development to match both harsh and unpredictable environmental conditions; (d) understanding evolved sex differences is critical for understanding the psychology of risky behavior; and (e) mismatches between current and past environments can dysregulate adolescent behavior, as demonstrated by age-segregated social groupings. The evolutionary model has broad implications for designing interventions for high-risk youth and suggests new directions for research that have not been forthcoming from other perspectives.