ITA: In che modo il nostro cervello è in grado di produrre quel tipo di comportamento flessibile e volto a specifici scopi che chiamiamo intelligenza? Le differenze cognitive tra individui sono dovute a una varietà di abilità mentali o a una sola? Questo articolo discute gli elementi centrali della teoria dell’intelligenza generale proposta da John Duncan nel volume How intelligence happens, tradotto recentemente in italiano e corredato da un capitolo conclusivo inedito. Prendendo le mosse dalla ricerca di Charles Spearman sull’intelligenza (...) generale e sui test d’intelligenza, Duncan caratterizza l’intelligenza nei termini di integrazione e controllo cognitivo. I dati neuroscientifici raccolti da Duncan suggeriscono che questi aspetti chiave del comportamento intelligente siano realizzati da un circuito cerebrale, chiamato multiple-demand system, in grado di scomporre problemi complessi in sotto-problemi più semplici e integrare informazioni da varie aree del cervello. ENG: How does our brain generate that sort of flexible and goal-directed behaviour that we call intelligence? Are individual differences in intelligence due to a variety of cognitive abilities or do they depend on one single mental ability? In this commentary, I revise and critically assess the key elements of John Duncan’s theory of general intelligence presented in the popular-science book How intelligence happens, recently translated into Italian and edited by F. Pavani, with a new final chapter. Starting from Charles Spearman’s research on a general intelligence factor and psychometric tests, Duncan advances a theory that characterises intelligence in terms of integration and cognitive control. Neuropsychological and neuroimaging data suggest that such key aspects of intelligent behaviour are realised by a brain network called a multiple-demand system, which is capable of decomposing complex problems into simpler sub-problems and then integrating information from different brain areas. (shrink)

Recent contributions to the philosophy of the social sciences have motivated ontological commitments using appeals to the social sciences (_naturalized_ social ontologies). These arguments rely on social scientific realism about the social sciences, the view that our social scientific theories are approximately true. I apply a distinction formulated in metaontology between ontologically loaded and unloaded meanings of existential quantification to argue that there is a pragmatic approach to naturalized social ontology that is minimally realist (it treats existence claims as true (...) or false) but that is ontologically austere. I argue that the extant arguments may be construed in terms of this pragmatic approach. The result is an approach to social ontology that is deflationist about naturalized social ontology. (shrink)

The success of any election depends on whether it was free and fair both to the candidates and the voters. Due to media coverage of national elections locally, regionally and globally, subtle psychological cues have become popular and are being used in student Representative Council (SRC) elections to harness voter preferences. This study focused on investigating the relationship between subtle psychological cues and voter preferences among university of Zimbabwe students. More so, the study was focused on four operationally defined subtle (...) psychological cues namely Ballot order effects, Hallo effects, Negativity bias and Push polls on whether they would influence the participant’s voter preference. The study takes the form of an experimental research design and is based on a sample of 80 purposefully selected participants. In addition, primary data was gathered using 4 ballot papers with a Likert scale and was analysed using Statistical Package for Social Studies (SPSS) version 23. Descriptive statistics, T-tests for independent samples, Chi-square tests and Pearson correlation were computed to establish the degree of the relationship between the variables in question. Results show that of the four subtle psychological cues under investigation, negativity bias and hallo effects were predominantly popular due to the American presidential debates such as that of Richard Nixon against Kennedy and Barack Obama against Hilary Clinton. In addition the results show no statistically significant group differences on how gender, ethnicity and year of study affected voter preferences. Ultimately, there were three positive correlations for the experiments Ballot order effects, Hallo effects and Negativity bias. However, contrary to the reviewed literature there was a negative correlation between Push polls and voter preferences. The conclusion was that there is statistically significant relationship between subtle psychological cues and voter preferences and hence have the potential to increase or decrease the votes a candidate obtains. Therefore, the University can closely monitor SRC elections and make sure the students do not abuse psychological cues such as negativity bias and push polls as they have the potential of ruining the student’s reputations. Also the organisation can add to its current SRC election policies the strategies that were implemented in this study to hold other factors at a constant such as using butterfly ballot paper ordering to help make the free and fair. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

The aim of this paper is to explore a new framework for personality assessment that may function as sanity nosology of personality traits: the Positive Personality Model. The recent publication of DSM-5 created the opportunity to assess personality traits as dimensional constructs (American Psychiatric Association, 2013). In Section III, five maladaptive personality traits are proposed as the maladaptive versions of Five Factor Model (FFM) traits (Costa and McCrae, 1985). This approach draws on the existing idea of conceptualizing pathological and typical (...) personality traits as part of a continuum. It places DSM-5’s maladaptive traits in a sickness pole and FFM’s traits in a “typical” pole. This spectrum, however, does not include a positive perspective that represents healthy behavior: a sanity nosology. The Positive Traits Inventory-5 (PTI-5; de la Iglesia and Castro Solano, 2018) is a measure designed to assess the positive reverse of the Personality Inventory for DSM-5-Adult (PID-5; Krueger, Derringer, Markon, Watson and Skodol, 2013). The 220 positive personality criteria were studied psychometrically using a sample of 1902 Argentinean adults from the general population (Mage = 39.10, SD = 13.81, Min = 18, Max = 83; 50.1% females, 49.9% males). Exploratory and confirmatory factor analyses resulted in a five-factor solution. The dimensions were labeled Sprightliness, Integrity, Serenity, Moderation, and Humanity and subsumed under the denomination of Positive Personality Model (PPM). Analyses of convergent validity provided some grounds for interpreting the five positive traits as positive versions of the pathological traits and the typical traits. When tested for its predictive capability on mental health, the PPM outperformed the variance explained by the FFM. It is concluded that the PPM may constitute a positive pole in the continuum of personality traits –possibly functioning as a sanity nosology– and that it is somewhat more related to optimal functioning than to typical trait models. The PPM should be confirmed in other populations, its predictive capability ought to be tested with other relevant variables, and longitudinal studies should be done to analyze the stability of the traits over time. (shrink)

In psychology, measurement instruments are constructed from scales, which are obtained on the grounds of exploratory and confirmatory factor analysis. Looking at the literature, one can find various recommendations regarding how these techniques should be used during the scale construction process. Some authors suggest to use exploratory factor analysis on the entire data set while others advice to perform an internal cross-validation by randomly splitting the data set in two and then either perform exploratory factor analysis on both parts or (...) exploratory factor analysis on the first part and confirmatory factor analysis on the other. In spite of all these divergent recommendations, there is no consensus on which method yields the best result. In this paper, we analyze this issue in light of the prediction versus accommodation debate and argue that the answer to this question depends on one’s conception of the criteria that should be used to achieve the goals of the scientific enterprise. (shrink)

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance (...) of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. (shrink)

The frequent occurrence of comorbidity has brought about an extensive theoretical debate in psychiatry. Why are the rates of psychiatric comorbidity so high and what are their implications for the ontological and epistemological status of comorbid psychiatric diseases? Current explanations focus either on classification choices or on causal ties between disorders. Based on empirical and philosophical arguments, we propose a conventionalist interpretation of psychiatric comorbidity instead. We argue that a conventionalist approach fits well with research and clinical practice and resolves (...) two problems for psychiatric diseases: experimenter’s regress and arbitrariness. (shrink)

This target article considers the relation of fluid cognitive functioning to general intelligence. A neurobiological model differentiating working memory/executive function cognitive processes of the prefrontal cortex from aspects of psychometrically defined general intelligence is presented. Work examining the rise in mean intelligence-test performance between normative cohorts, the neuropsychology and neuroscience of cognitive function in typically and atypically developing human populations, and stress, brain development, and corticolimbic connectivity in human and nonhuman animal models is reviewed and found to provide evidence of (...) mechanisms through which early experience affects the development of an aspect of cognition closely related to, but distinct from, general intelligence. Particular emphasis is placed on the role of emotion in fluid cognition and on research indicating fluid cognitive deficits associated with early hippocampal pathology and with dysregulation of the hypothalamic-pituitary-adrenal axis stress-response system. Findings are seen to be consistent with the idea of an independent fluid cognitive construct and to assist with the interpretation of findings from the study of early compensatory education for children facing psychosocial adversity and from behavior genetic research on intelligence. It is concluded that ongoing development of neurobiologically grounded measures of fluid cognitive skills appropriate for young children will play a key role in understanding early mental development and the adaptive success to which it is related, particularly for young children facing social and economic disadvantage. Specifically, in the evaluation of the efficacy of compensatory education efforts such as Head Start and the readiness for school of children from diverse backgrounds, it is important to distinguish fluid cognition from psychometrically defined general intelligence. (Published Online April 5 2006) Key Words: cognition; cognition-emotion reciprocity; developmental disorders; emotion; fluid cognition; Flynn effect; general intelligence; limbic system; neuroscience; phenylketonuria; prefrontal cortex; psychometrics; schizophrenia. (shrink)

Ability and achievement are not traits: they are relations. Mistaking traits for relations has a history even in science (our understanding of gravity). This mistake is possibly responsible for the lackluster performance of the results of our educational research when we have tried to use it to inform policy. It is particularly troublesome for interventions that target “children at risk.” The paper provides a quasi-formal outline of achievement as a relation and it then uses the outline to explain some problematic (...) research findings. (shrink)

First-generation students are more likely to feel misplaced and struggle at university than students with university-educated parents. We assumed that the shutdowns during the Coronavirus-pandemic would particularly threaten FGS due to obstructed coping mechanisms. Specifically, FGS may show lower identification with the academic setting and lower perceived fairness of the university system. We investigated whether FGS and CGS used different defenses to cope with the shutdown threat in a large sample of German-speaking students. Using Structural Equation Modeling, we found that (...) for all students, independent of academic parental background, high levels of system justification were associated with perceiving the learning situation as less threatening, better coping with failure, and less helplessness. However, in comparison to CGS, FGS showed small but significant reductions in system justification and relied more on concrete personal relationships with other students as well as their academic identity to cope with the threatening situation. We discuss implications for helping FGS succeed at university. (shrink)

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of (...) latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. (shrink)

Exploratory factor analysis is a statistical method widely used in quantitative psychology for the construction of scales and measurement instruments. It aims to reduce the complexity of a data set and explain the common and unique variance using latent variables. In introductory textbooks, exploratory factor analysis is generally presented in contrast to confirmatory factor analysis as a theory- or a hypothesis-generating process that does not require prior background, theory or hypothesis to be performed. The aim of the present paper is (...) to analyze this claim and clarify in which sense exploratory factor analysis is theory-laden. We provide a careful examination of the concepts it involves and thereby establish a clear limitation of the epistemic scope of exploratory factor analysis. (shrink)

The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory, in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a radically different conceptualization in terms of a network approach, where comorbidity is hypothesized to (...) arise from direct relations between symptoms of multiple disorders. We propose a method to visualize comorbidity networks and, based on an empirical network for major depression and generalized anxiety, we argue that this approach generates realistic hypotheses about pathways to comorbidity, overlapping symptoms, and diagnostic boundaries, that are not naturally accommodated by latent variable models: Some pathways to comorbidity through the symptom space are more likely than others; those pathways generally have the same direction (i.e., from symptoms of one disorder to symptoms of the other); overlapping symptoms play an important role in comorbidity; and boundaries between diagnostic categories are necessarily fuzzy. (shrink)

This paper is a conceptual analysis of the theory debate in psychology, as carried out by cognitivists and radical behaviorists. The debate has focused on the necessity of theories in psychology. However, the logically primary issue is the nature of theories, or what theories are. This claim stems from the fact that cognitivists and radical behaviorists adopt disparate accounts of the nature of theories. The cognitivists' account is closely akin to the received view from logical positivism, where theories are collections (...) of statements and theoretical terms are restricted to designate unobservable entities. Radical behaviorists also conceive theories as collections of statements, but restrict theoretical terms in psychology to designate observable entities. If each side approaches the necessity issue with its preferred account, both agree that theories are necessary in psychology. Hence, there is no disagreement over the necessity of theories in psychology per se, only over the nature of theories. The received view, however, has been shown to suffer from irreparable difficulties that have led to its total rejection in post-positivistic philosophy of science. Alternative accounts, like the structuralist and semantic views, do not raise the issue of whether theories are necessary in psychology. (shrink)

In this paper, we consider how latent variables of mainstream quantitative psychology fits with two different models of scientific kinds. On the one hand, there is a good reason to think they fit with taxonomic and predictive success criteria that are popular within an epistemic understanding of scientific kinds. On the other hand, they conflict with widely shared person-based ontological commitments that underwrite psychological kinds because this research rests in large part on between-individual studies. We explore the implications of the (...) different views on scientific kinds and argue that this is indeed a dilemma for the scientific discipline of psychology. (shrink)

Psychotherapy research is known for its pursuit of evidence-based treatment. Psychotherapeutic efficacy is assessed by calculation of aggregated differences between pre treatment- and post treatment symptom levels. As this ‘gold standard methodology’ is regarded as ‘procedurally objective’, the efficacy number that results from the procedure is taken as a valid indicator of treatment efficacy. However, I argue that the assumption of procedural objectivity is not justified, as the methodology is build upon a problematic numerical basis. I use an empirical case (...) study to show how measurement problems practically occur in the first step of data collection, i.e. in individual symptom measurement. These problems have been discussed and acknowledged for decades, but still measurement is regarded as the best epistemic means to gain evidence on psychotherapeutic efficacy. Therefore, I show how initial measurement problems are overlooked in the remainder of the methodological procedure, which harms the ‘evidence-base’ of psychotherapeutic EBT. Via this applied analysis, I exhibit concerns that are increasingly raised in the literature in an empirical way, to emphasize the need for a non-idealized consideration of the ‘gold standard methodology’ as a means towards its clinical end. (shrink)

With regard to the topicality of corporate social responsibility in retail practice, only a few studies have comprehensively analyzed the role of CSR in retail. Due to the specific role of a retailer as a gatekeeper between the producer and the consumer in the supply chain, a comprehensive understanding of the impact of consumer perceptions of CSR activities is of great relevance. Therefore, this study contributes information regarding the impact of CSR activities on retailer performance. Using a comprehensive conceptualization of (...) CSR, the results of our customer survey suggest that CSR has positive implications as driver of customer loyalty and favorable consumer purchasing behavior. The authors demonstrate the CSR dimensions that are most important for retailers to influence positively consumer purchasing behavior. This study highlights the significance of the credibility of retailer CSR activities and show that consumers’ CSR orientation impacts the relationship between retailer CSR activities and consumer behavior. (shrink)

Scientific psychology involves both identifying and classifying phenomena of interest (description) and revealing the causes and mechanisms that contribute towards these phenomena arising (explanation). Within personality psychology, some propose that aspects of behavior and cognition can be explained with reference to personality traits. However, certain conceptual and logical issues cast doubt upon the adequacy of traits as coherent explanatory constructs. This paper discusses ?explanation? in psychology and the problems of circularity and reification. An analysis of relations and intrinsic properties is (...) then developed to address the logical requirements necessary for circumventing these problems. An examination of McCrae and Costa's defense of traits as explanatory constructs, in terms of ?tendencies? and ?dispositions? highlights logical issues that prevent traits, so defined, from explaining trait-like behaviors and cognitions. The logical requirements for a coherent trait-explanatory account are outlined and possible explanatory directions in trait-approaches are discussed. The ongoing tendency towards fallacious reasoning in psychology and suggestions for preventing this are further examined. (shrink)

Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned – that is, that the two must refer to roughly the same set of hypothetical observations. Here, I argue that many applications of statistical inference in psychology fail to meet this basic condition. Focusing on the most widely used (...) class of model in psychology – the linear mixed model – I explore the consequences of failing to statistically operationalize verbal hypotheses in a way that respects researchers' actual generalization intentions. I demonstrate that although the “random effect” formalism is used pervasively in psychology to model intersubject variability, few researchers accord the same treatment to other variables they clearly intend to generalize over (e.g., stimuli, tasks, or research sites). The under-specification of random effects imposes far stronger constraints on the generalizability of results than most researchers appreciate. Ignoring these constraints can dramatically inflate false-positive rates, and often leads researchers to draw sweeping verbal generalizations that lack a meaningful connection to the statistical quantities they are putatively based on. I argue that failure to take the alignment between verbal and statistical expressions seriously lies at the heart of many of psychology's ongoing problems (e.g., the replication crisis), and conclude with a discussion of several potential avenues for improvement. (shrink)

Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are (...) applied to daily diary data ( Median = 94 days) of maladaptive behaviors collected from a sample ( N = 101) of individuals diagnosed with personality disorders (PDs). Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing–Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Disinhibition structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic. (shrink)

Within evolutionary biology, life-history theory is used to explain cross-species differences in allocation strategies regarding reproduction, maturation, and survival. Behavioral scientists have recently begun to conceptualize such strategies as a within-species individual characteristic that is predictive of behavior. Although life history theory provides an important framework for behavioral scientists, the psychometric approach to life-history strategy measurement—as operationalized by K-factors—involves conceptual entanglements. We argue that current psychometric approaches attempting to identify K-factors are based on an unwarranted conflation of functional descriptions and (...) proximate mechanisms—a conceptual mix-up that may generate unviable hypotheses and invites misinterpretation of empirical findings. The assumptions underlying generic psychometric methodology do not allow measurement of functionally defined variables; rather these methods are confined to Mayr’s proximate causal realm. We therefore conclude that K-factor scales lack validity, and that life history strategy cannot be identified with psychometrics as usual. To align theory with methodology, suggestions for alternative methods and new avenues are proposed. (shrink)

Management scholars have paid close attention to the construct of organizational or corporate reputation, particularly in the applied business ethics and corporate social responsibility fields. Extant research demonstrates that CR is one of the key mediators between CSR and important organizational outcomes, which ultimately improve organizational performance. Yet, hitherto the research focused on CR construct has been plagued by multiple definitions, conflicting conceptualizations, and unclear operationalizations. The purpose of this article is to provide theoretical ground for positioning of CR as (...) an assessment construct that is modeled as a second-order factor affecting individual first-order dimensions, and to provide methodological and empirical support toward such conceptualization. We assert that intangible, socially complex, and causally ambiguous CR can be accurately estimated through its individual measurable dimensions. Using survey data from Peru, we empirically test the hypothesized second-order reflective model within a hierarchy of nested and non-nested models, and compare its model fit and predictive power with alternative conceptualizations. Modeling CR as a second-order reflective construct relies on a set of theoretical propositions and yields several methodological advantages, including strong conceptual interpretability and parsimony when tested within a nomological context. We explicitly demonstrate positive organizational outcomes of CR: customer trust, corporate identification, in-role behavior, and extra-role behavior. Then, we demonstrate that the shorter scales of CR can be used as a good proxy for the full construct measure. The paper concludes by highlighting theoretical insights, and methodological and managerial implications of the findings. (shrink)

Psychometrics is one of the main approaches to social scientific measurement. It is relied upon in drug testing, economic policymaking, recruitment, and other decision-making contexts. The first aim of this article is to introduce philosophers to key aspects of psychometrics, namely, classical test theory, item response theory, and construct validity. The second aim is to show how a debate on the nature of psychological attributes manifests in psychometrics. In this debate, realists claim that psychometric measures are indicators of independently existing (...) qualities, while operationalists argue that a measure defines its target attribute. The third and final aim is to argue that despite its poor reputation among philosophers, operationalism is a viable approach to psychometrics. (shrink)

Despite the miraculous progress of science—it’s practitioners continue to run into mistakes, either discrediting research unduly or making leaps of causal inference where none are warranted. In this we isolate two of the reasons for such behavior involving the misplaced understanding of the role of mechanisms and mechanistic knowledge in the establishment of cause-effect relationships. We differentiate causal knowledge into causes, effects, mechanisms, cause-effect relationships, and causal stories. Failing to understand the role of mechanisms in this picture, including their absence (...) of knowledge or incorrect specification, leads to errors of wrongly excluding cause-effect relationships or wrongly inferring their existence. We highlight the primary of causality over mechanistic knowledge and causal stories in scientific reasoning. (shrink)

Network analysis is a promising step forward in efforts to align psychological assessment with explanatory theory in psychological science. The implications of Cramer et al.'s analysis are quite general. Networks analysis may illuminate functional relations not only among observable behaviors that comprise psychological disorders, but among cognitive and affective processes that causally contribute to everyday experience and action.

The present study tested the assumption that self-ratings, such as those used for measuring state anxiety, do not measure a one-dimensional transcendent entity but involve decisions based on a multi-dimensional judgment. Two groups of subjects were presented with a balanced nine-item state anxiety questionnaire. Each group received a different set of instructions (a standard set and an altered instruction set suggesting unidimensionality of the questions in the questionnaire). It was hypothesized that this change in instructions would impact the structure of (...) the data. The impact of the instructions was detectable at the level of the observed correlation between the negative and positive composites, Cohen's (1988) q=-0.27$. A multigroup confirmatory factor analysis showed that positive and negative wording factors correlated more strongly when unidimensionality was suggested than when standard instructions were used, q=-0.54. Theoretical and practical implications are discussed. (shrink)

The Representational Theory of Measurement is the best known account of the kind of representation measurement requires. However, RTM has been challenged from various angles, with critics claiming e.g. that RTM fails to account for actual measurement practice and that it is ambiguous about the nature of measurable attributes. In this paper I use the critical literature on RTM to formulate Representation Minimalism – a characterization of what measurement-relevant representation requires at the minimum. I argue that Representation Minimalism avoids the (...) main problems with RTM while acknowledging its usefulness as the formal foundation of representation in measurement. (shrink)

This paper applies conceptual engineering to deal with four objections that have been levelled against operationalism in psychology. These objections are: operationalism leads to harmful proliferation of concepts, operationalism goes hand-in-hand with untenable antirealism, operationalism leads to arbitrariness in scientific concept formation, and operationalism is incompatible with the usual conception of scientific measurement. Relying on a formulation of three principles of conceptual engineering, I will argue that there is a useful form of operationalism that does not fall prey to these (...) four objections. (shrink)

Emotional experiences typically labelled “being moved” or “feeling touched” may belong to one universal emotion. This emotion, which has been labelled “kama muta”, is hypothesised to have a positive valence, be elicited by sudden intensifications of social closeness, and be accompanied by warmth, goosebumps and tears. Initial evidence on correlations among the kama muta components has been collected with self-reports after or during the emotion. Continuous measures during the emotion seem particularly informative, but previous work allows only restricted inferences on (...) intra-individual processes because time series were cross-correlated across samples. In the current studies, we instead use a within-subject design to replicate and extend prior work. We compute intra-individual cross-correlations between continuous self-reports on feeling moved and (1) positive and negative affect; (2) goosebumps and subjective warmth and (3) appraisals of closeness and morality. Results confirm the predictions of kama muta theory that feeling moved by intensified communal sharing cross-correlates with appraised closeness, positive affect, warmth and (less so) goosebumps, but not with negative affect. Contrary to predictions, appraised morality cross-correlated with feeling moved as much as appraised closeness did. We conclude that strong inferences on emotional processes are possible using continuous measures, replace earlier findings, and are largely in line with theorising. (shrink)

Researchers rely on psychometric principles when trying to gain understanding of unobservable psychological phenomena disconfounded from the methods used. Psychometric models provide us with tools to support this endeavour, but they are agnostic to the meaning researchers intend to attribute to the data. We define method effects as resulting from actions which weaken the psychometric structure of measurement, and argue that solution to this confounding will ultimately rest on testing whether data collected fit a psychometric model based on a substantive (...) theory, rather than a search for a model that best fits the data. We highlight the importance of taking the notions of fundamental measurement seriously by reviewing distinctions between the Rasch measurement model and more generalised 2PL and 3PL IRT models. We then present two lines of research that highlight considerations of making method effects explicit in experimental designs. First, we contrast the use of experimental manipulations to study measurement reactivity during the assessment of metacognitive processes with factor-analytic research of the same. The former suggests differential performance-facilitating and -inhibiting reactivity as a function of other individual differences, whereas factor-analytic research suggests a ubiquitous monotonically predictive confidence factor. Second, we evaluate differential effects of context and source on within-individual variability indices of personality derived from multiple observations, highlighting again the importance of a structured and theoretically grounded observational framework. We conclude by arguing that substantive variables can act as method effects and should be considered at the time of design rather than after the fact, and without compromising measurement ideals. (shrink)

Competing perspectives on the nature of emotion are illustrated with latent and emergent variable models. Latent variable models draw from classical test theory, assuming that the measured indicators of emotion covary by virtue of some common executive, organizing neural circuit or network in the brain. By contrast, emergent variable models draw from a theory-driven, operational definition tradition, positing that emotions do not cause, but rather are caused by, the measured indicators of emotion, assuming no executive neural circuit or network, and (...) requiring no covariation among indicators. I suggest that the emergent variable model may be more compatible with the extant literature on the nature of emotion, especially in the age of affective neuroscience. (shrink)

Within the corporate social responsibility research field, the construct of organizational reputation has been extensively scrutinized as a crucial mediator between the firm CSR engagement and valuable organizational outcomes. Yet, the existing literature on organizational reputation suffers from substantive divergence between the studies in terms of defining the construct’s domain, dimensional structure, and the methodological operationalization. The current study aims to refine the organizational reputation construct by reconciling varying theoretical perspectives within the construct’s definitional landscape, suggesting a holistic but parsimonious (...) triadic view on the organizational reputation construct for customer stakeholders. Based on commonly used extant organizational reputation measures, we theoretically and empirically develop the customer-based triadic organizational reputation scale and position it as a superordinate multidimensional construct influencing three distinct first-order dimensions: product and service efficacy, societal ethicality, and market prominence. Results show that the proposed triadic conceptualization of organizational reputation is theoretically defensible, and the resulting scale is cross-culturally generalizable and performs well compared with existing, longer measures of organizational reputation. Together, the organizational reputation model developed here suggests that, for cognitive economy and functional efficiency, customers will access a second-order reflective model of organizational reputation as the default implicit attitude, which in turn will activate reflections of the implicit attitude in the form of first-order dimensions. (shrink)

Psychological constructs such as personality dimensions or cognitive traits are typically unobserved and are therefore measured by observing so-called indicators of the latent construct. The Common Factor Model models the relations between the observed indicators and the latent variable. In this article we argue in favor of interpreting the CFM as a causal model rather than merely a statistical model, in which common factors are only descriptions of the indicators. When there is sufficient reason to hypothesize that the underlying causal (...) structure of the data is a common cause structure, a causal interpretation of the CFM has several benefits over a merely statistical interpretation of the model. We argue that a causal interpretation conforms with most research questions in which the goal is to explain the correlations between indicators rather than merely summarizing them; a causal interpretation of the factor model legitimizes the focus on shared, rather than unique variance of the indicators; and a causal interpretation of the factor model legitimizes the assumption of local independence. (shrink)