To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The combination of human forecasters’ subjective probability estimates usually improves upon the estimates provided by individual forecasters. In order to combine the probability estimates in a Bayes optimal way, prior work proposed a normative Bayesian fusion model that models the estimates with a beta distribution conditioned on their truth value. However, this model assumes conditionally independent probability estimates, although estimates provided by different forecasters are usually correlated. Here, we introduce a Bayesian model for combining subjective probability estimates that explicitly considers their correlation. We assume that an estimate provided by a forecaster for a given query depends on both the forecaster’s skill and the query’s difficulty. The correlation between probability estimates provided by different forecasters is assumed to be caused by the queries that make the forecasters provide similar estimates, for example, correct and highly confident estimates for very easy queries. Our model represents the probability estimates with a beta distribution conditioned on their truth value. It explicitly models the forecasters’ skills and the queries’ difficulties with skill parameters specific for each forecaster and difficulty parameters specific for each query. In this way, it can model the correlations between probability estimates and consider it when combining the estimates. Evaluations on a data set consisting of the subjective probability estimates of 85 human forecasters for 180 queries show improved fusion performance in terms of Brier score compared to related Bayesian fusion models. In particular, it outperforms independent fusion models that suffer from overconfidence.
Irritability is a core symptom and diagnostic criterion in several childhood psychiatric disorders. Research has documented bidirectional associations between child irritability and parenting practices; however, cultural variations in these associations remain underexplored.
Using three-wave longitudinal data (N = 2,408) from the Future of Families and Child Wellbeing Study (FFCWS) in the United States, this study examined associations between child irritability, parenting behaviors (psychological aggression, physical assault, neglect, and non-violent discipline) and parenting stress across three racial–ethnic groups: non-Latine Black (n = 1,167; 605 males), non-Latine White (n = 614; 314 males), and Latine (n = 627; 316 males) using cross-sectional and temporal network analyses.
Parenting behaviors and stress were associated with child irritability concurrently and longitudinally across groups. Results showed bidirectional effects between parenting behaviors/stress and child irritability across ages 3, 5, and 9, with more similarities than differences between groups. Physical assault and lower use of non-violent discipline predicted higher future child irritability (partial correlations = 0.03–0.18 for physical assault and 0.04–0.07 for non-violent discipline) across racial–ethnic groups.
These findings suggest parenting interventions may be scalable across cultural contexts to promote positive child outcomes and well-being, though future work should elucidate culturally specific factors that inform tailored practices.
This study explores the complex interplay between academic, social and cultural pressures and the mental health of female university students in Pakistan. Operating within a collectivist society, these students face unique challenges, including high academic expectations, financial constraints and rigid gender roles, which significantly increase their vulnerability to psychological distress, anxiety and depression. Despite the high prevalence of these issues, help-seeking behaviours remain markedly low. This research investigates the formidable barriers to seeking professional psychological support, focusing on the potent influence of pervasive social stigma, fear of reputational damage and a widespread lack of mental health literacy. Cultural norms that prioritize family honour and misinterpret emotional suffering as personal weakness further compound these obstacles, often leading to silence and isolation. Utilizing a qualitative approach, this paper highlights the critical need for culturally sensitive, university-based mental health interventions. Recommendations include establishing accessible on-campus counselling services, implementing de-stigmatization awareness campaigns and integrating mental health education into the academic curriculum to foster a more supportive environment and encourage proactive help-seeking among this demographic.
The study examines the influence of bilingual experience, age and verbal working memory (WM) on the comprehension of passive voice by 116 typically developing (TD) and 65 autistic children aged 3 to 13, who were tested in their societal languages, German or French. Some children were mainly exposed to the societal language while some children were also exposed to other languages. We adopt a continuous approach to bilingual experience and operationalize it as a balance of cumulative exposure, measured through entropy scores. We found that the comprehension of passive voice improved with age in both groups, and higher verbal WM predicted better performance in autistic but not TD children. Although autistic children were less accurate than TD children, bilingual experience did not contribute to the differences between the two groups. These findings suggest that bilingualism has no detrimental effect on the comprehension of complex syntactic structures in autistic children.
The current study investigated two heuristic processing strategies, the agent-first strategy and an animacy-based strategy, in visual world eye-tracking data as well as sentence final interpretations of wh-questions in adolescent L1 German learners of English in both their L1 and their L2. We observed differences between online and offline measures, as well as L1-L2 differences, both in the selection and the time course of application of the heuristics. In L1 German, heuristics were visible only in online data, and the dominant heuristic was animacy-based. In L2 English, the animacy-based heuristic was applied later and to a lesser degree than the agent-first heuristic. The results speak against a direct transfer of heuristic strategies from the L1 to the L2. Instead, we suggest that low-proficiency learners may not have the capacity to use several heuristics at once, and may thus prioritize the agent-first strategy due to its broad domain of application.
This study investigates how lexical, phrasal, and contrastive stress are acoustically realized in American English, focusing on whether men and women differ in how they use pitch, amplitude, and duration to convey stress. Thirty-six native speakers completed minimal-pair stress production tasks online. We analyzed the resulting speech using prosodic contour measures, Bayesian ANOVAs, mixed-effects regression, Random Forest Classification, and human coder judgments. Results show greater acoustic overlap between lexical and contrastive stress than between either of those and phrasal stress. Duration was the primary cue for phrasal stress, while lexical and contrastive stress relied more evenly on multiple cues. Gender-based differences were especially evident in contrastive stress, which, to our knowledge, has not previously been studied in relation to gender: women relied more on pitch, while men emphasized amplitude and duration. These findings highlight the multidimensional acoustic nature of stress realization and demonstrate the value of combining computational and perceptual approaches in prosody research.
Models of mind as computational processes in the brain have some attractive features, but are ultimately unviable. One fundamental reason is that they cannot account for representation in and for the organism itself, but only at best for some outside programmer or user – they cannot account for representational normativity. A model of the emergence of such normativity is outlined and shown to yield a model of functional brain processes as oscillatory processes that modulate other such processes. This is in fact what is found in studies of brain processes, and these phenomena are at best anomalous for any kind of computational model.
The computer metaphor invites views on mental, neural, and behavioral processes built around the input–output relations between an inner and an outer domain usually cast in terms of information processing. This metaphor also operates in ways that make the material constitution and context of these processes and domains less relevant. There are two problems here. First, the metaphor suggests that we know more about these processes and domains than we actually do. Second, the metaphor also shields this unwarranted confidence from the life sciences’ broader empirical context, which provides examples and conceptual frameworks that bear critically on much work within the cognitive, neural, and behavioral sciences. In both ways, the computer metaphor limits the range of conceptual and empirical options to make further progress. By discarding the computer metaphor and positioning the various cognitive sciences within the general life science domain, new views on minds, brains, and behavior become possible that have a closer fit to the other sciences. The early evolution of the nervous systems will be used as a showcase that provides new approaches to understanding cognitive and experiential phenomena.
Mental health promotion in schools has gained greater salience in high-income countries, especially since the COVID-19 pandemic. However, less is known about its conceptualisation and implementation in less developed countries such as Indonesia. This research aimed to describe what school communities in Surabaya, Indonesia, understand about their role and actions in promoting mental health. This exploratory study employed Focus Group Discussions with diverse members of junior high school communities, including students. Using the Health Policy Triangle as the theoretical framework, transcripts were thematically analysed using a deductive approach. Forty-six participants took part, from national to municipality levels. Three themes were found. First, participants considered that socialisation difficulties contributed to poor student mental health and engagement in learning. Second, while schools reported familiarity with a range of actions, from promotion to preventive and curative interventions, their primary focus was around ensuring access to services for students with mental health problems. Third, contextual barriers and enablers were identified impacting schools’ mental healthpromoting actions. The inter-related aspects of context, content, process, and actors were found to shape implementation. These findings highlight the multi-component expertise and resources of school communities, which, if better embraced, could enhance their capabilities to promote mental health in schools.
The computer metaphor is a central component of the narrative in cognitive psychology and cognitive neuroscience since the 1960s, although the interpretations of the metaphor are not homogeneous, and many of them are not even compatible. However, the general take is that the brain processes inputs to deliver appropriate outputs using a roughly computational strategy. Namely, the brain somehow encodes inputs, manipulates them following some algorithms, stores some information extracted from those inputs, recombines some bits of that information, delivers the proper commands for accurate outputs, and so on. The computer metaphor has offered decades of theoretical progress and many computational methods and models within the cognitive sciences. However, it similarly faces longstanding problems that cyclically bring into question the usefulness of the metaphor to guide the scientific approach to fundamental (and not-so-fundamental) issues in the sciences of the mind. Here, I defend an alternative metaphor inspired by the use of the notion of resonance in cognitive science and neuroscience and more concretely based on the notion of ecological resonance developed in the literature of ecological psychology.
The pervasive computer metaphor of mind and brain shapes our understanding of key cognitive concepts. These include the concept of “metaphor,” usually treated as a mapping between structures within knowledge representations. But metaphors understood performatively directly guide our embodied practice. This essay analyzes how the computer the metaphor of mind and brain shaped our activities as researchers in the cognitive sciences. I highlight the positive contributions of the metaphor and its detrimental effect of disengaging us as scientists from research on the most vital aspects of cognition: behavior, experience, and the ability to create and use symbolic forms. I will then explore whether a pragmatic understanding of metaphors could help identify an alternative – a metaphor that establishes practices in the sciences of mind and brain, which can address the fundamental contemporary challenges.
We aim to move beyond or at least to the side of the computer metaphor for mind and brain. We are not looking to demolish or banish it for those who find it useful, but instead, we want to articulate alternative metaphorical paths for advancing cognitive science. Despite decades of critique, it is striking how entrenched this metaphor remains (Newman, 2024). Does it continue like a Superman, impervious to critique, or does it stagger forward like a ragged puppet controlled by insistent operators? Given its survival in the face of much criticism, perhaps we are foolish to seek alternatives. Yet, we were born into a wealth of evidence and argument pointing to the computer metaphor’s deep inadequacy in explaining the complexities of mind and brain. Earlier generations may have seen the computer metaphor as the only path forward in cognitive science. But many of our mentors, having been trained in computational psychology, later turned against it. We suspect its persistence in some corners is less about its merits and more about the lack of widely known alternatives.