CATECHIZING THE HEAD AND THE HEART: AN INTEGRATED MODEL FOR CONFIRMATION MINISTRY

In catechesis for adolescents seeking confirmation in the Roman Catholic Church, a dualistic bias unconsciously dichotomizes objective doctrine and subjective psychology. This is problematic because if a catechist does not communicate mind‐independent truth, no seed of Catholic faith will have been planted in a student. At the same time, if a catechist does not affirm a student's subjectivity, the seed cannot find receptive soil. I believe the key to integrating these intellectual and affective elements – the head and the heart – lies in the link between what Bernard Lonergan calls authentic subjectivity and objectivity. Catechists can appeal to this link by embracing the moral responsibility to ‘know our knowing,’ becoming aware of our dualistic bias and judging our faith experiences according to objective standards of knowledge.     

The self-fulfilling influence of mother expectations on children's underage drinking

This research examined whether mothers' expectations about their children's drinking behavior influenced their children's future alcohol use through self-fulfilling prophecies. It also investigated whether children's self-esteem, family social class, or the valence of mother expectations moderated this process. Analyses of longitudinal data from 505 mother-child dyads yielded results consistent with a self-fulfilling prophecy. The inaccurate portion of mother expectations predicted children's future alcohol use after accounting for relevant control variables. Moderation analyses indicated that this effect was stronger among higher self-esteem children and when mother expectations were positively valenced (i.e., when mothers underestimated their children's future alcohol use). The findings are discussed in terms of parent-child relationship quality, peer influences, self theories, and out-group stereotypes.     

Intracerebroventricular Administration of Mineralocorticoid Receptor Antisense Oligonucleotides Attenuates Salt Appetite in the Rat

The anterior ventral third ventricle (AV3V) region of the brain contains high concentrations of mineralocorticoid receptors (MR) and glucocorticoid receptors (GR) that are important in the maintenance of body fluid and electrolyte balance as well as other physiological processes. Daily intracerebroventricular pulse injections of MR antisense oligonucleotides significantly suppressed deoxycorticosterone acetate (DOCA) induced salt appetite in a dose-related manner. Similar administration of GR antisense or scrambled/sense oligonucleotide into the third ventricle failed to inhibit salt appetite. Salt appetite aroused after adrenalectomy was not suppressed by MR antisense oligonucleotide treatments but was suppressed by an antisense oligonucleotide directed against the angiotensin II AT1 receptor subtype. Receptor binding analysis demonstrated that MR and GR oligonucleotide treatments each reduced their respective receptor subtypes. Finally, although GR antisense oligonucleotide treatment was ineffective in suppressing DOCA-induced salt appetite, this treatment did increase stress induced corticosterone release as well as delayed the recovery of corticosterone to basal levels after stress.     

Personality Research and Assessment in the Era of Machine Learning

The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.     

Linear correlates in the speech signal: the orderly output constraint

Neuroethological investigations of mammalian and avian auditory systems have documented species-specific specializations for processing complex acoustic signals that could, if viewed in abstract terms, have an intriguing and striking relevance for human speech sound categorization and representation. Each species forms biologically relevant categories based on combinatorial analysis of information-bearing parameters within the complex input signal. This target article uses known neural models from the mustached bat and barn owl to develop, by analogy, a conceptualization of human processing of consonant plus vowel sequences that offers a partial solution to the noninvariance dilemma--the nontransparent relationship between the acoustic waveform and the phonetic segment. Critical input sound parameters used to establish species-specific categories in the mustached bat and barn owl exhibit high correlation and linearity due to physical laws. A cue long known to be relevant to the perception of stop place of articulation is the second formant (F2) transition. This article describes an empirical phenomenon--the locus equations--that describes the relationship between the F2 of a vowel and the F2 measured at the onset of a consonant-vowel (CV) transition. These variables, F2 onset and F2 vowel within a given place category, are consistently and robustly linearly correlated across diverse speakers and languages, and even under perturbation conditions as imposed by bite blocks. A functional role for this category-level extreme correlation and linearity (the "orderly output constraint") is hypothesized based on the notion of an evolutionarily conserved auditory-processing strategy. High correlation and linearity between critical parameters in the speech signal that help to cue place of articulation categories might have evolved to satisfy a preadaptation by mammalian auditory systems for representing tightly correlated, linearly related components of acoustic signals.