Searching for Prosociality in Qualitative Data: Comparing Manual,Closed-Vocabulary,and Open-Vocabulary Methods

Although most people present themselves as possessing prosocial traits, people differ in the extent to which they actually act prosocially in everyday life. Qualitative data that were not ostensibly collected to measure prosociality might contain information about prosocial dispositions that is not distorted by self-presentation concerns. This paper seeks to characterise charitable donors from qualitative data. We compared a manual approach of extracting predictors from participants' self-described personal strivings to two automated approaches: A summation of words predefined as prosocial and a support vector machine classifier. Although variables extracted by the support vector machine predicted donation behaviour well in the training sample (N = 984), virtually, no variables from any method significantly predicted donations in a holdout sample (N = 496). Raters' attempts to predict donations to charity based on reading participants' personal strivings were also unsuccessful. However, raters' predictions were associated with past charitable involvement. In sum, predictors derived from personal strivings did not robustly explain variation in charitable behaviour, but personal strivings may nevertheless contain some information about trait prosociality. The sparseness of personal strivings data, rather than the irrelevance of open-ended text or individual differences in goal pursuit, likely explains their limited value in predicting prosocial behaviour. © 2020 European Association of Personality Psychology     

Psychometric and Validity Issues in Machine Learning Approaches to Personality Assessment: A Focus on Social Media Text Mining

In the age of big data, substantial research is now moving toward using digital footprints like social media text data to assess personality. Nevertheless, there are concerns and questions regarding the psychometric and validity evidence of such approaches. We seek to address this issue by focusing on social media text data and (i) conducting a review of psychometric validation efforts in social media text mining (SMTM) for personality assessment and discussing additional work that needs to be done; (ii) considering additional validity issues from the standpoint of reference (i.e. ‘ground truth’) and causality (i.e. how personality determines variations in scores derived from SMTM); and (iii) discussing the unique issues of generalizability when validating SMTM for personality assessment across different social media platforms and populations. In doing so, we explicate the key validity and validation issues that need to be considered as a field to advance SMTM for personality assessment, and, more generally, machine learning personality assessment methods. © 2020 European Association of Personality Psychology     

Disentangling the far transfer of language comprehension gains using latent mediation models

While we know that interventions targeting oral language can be effective, little is known about what drives these effects. In this study, we examine whether gains in transfer measures are mediated through the specific words that are trained in a language intervention. Based on a large‐scale randomized controlled trial of language intervention in 4‐ to 5‐year‐old children, latent mediation models were used to disentangle oral language gains in transfer measures. The results first showed that the effects of the language intervention and the transfer effects are generated through expressive rather than receptive measures of language. Second, we found that the effects of the intervention on intermediate transfer measures of language were mediated through the ability to define the trained words. Third, and critically, for far transfer measures that did not contain any of the trained words, the effects were mediated through the trained words. The findings relate to theories of transfer and support the idea that far transfer is possible, at least within the same domain. In addition, it seems that effects on receptive language skills are difficult to obtain and that what is improved is instead the children's ability to express themselves and use procedures to explain words. Thus, to optimize intervention effects, future studies should focus on expressive language.     

On the Consistency of the Δ1 1-CA Fragment of Frege's Grundgesetze

It is well known that Frege's system in the Grundgesetze der Arithmetik is formally inconsistent. Frege's instantiation rule for the second-order universal quantifier makes his system, except for minor differences, full (i.e., with unrestricted comprehension) second-order logic, augmented by an abstraction operator that abides to Frege's basic law V. A few years ago, Richard Heck proved the consistency of the fragment of Frege's theory obtained by restricting the comprehension schema to predicative formulae. He further conjectured that the more encompassing ¹ ₁-comprehension schema would already be inconsistent. In the present paper, we show that this is not the case.