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30,703 result(s) for "Individuality."
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In the Absence of the Gift
By adopting ideas like \"development,\" members of a Papua New Guinean community find themselves continuously negotiating what can be expected of a relative or a community member. Nearly half the people born on the remote Mbuke Islands become teachers, businessmen, or bureaucrats in urban centers, while those who stay at home ask migrant relatives \"What about me?\" This detailed ethnography sheds light on remittance motivations and documents how terms like \"community\" can be useful in places otherwise permeated by kinship. As the state withdraws, Mbuke people explore what social ends might be reached through involvement with the cash economy.
Collectivism predicts mask use during COVID-19
Since its outbreak, COVID-19 has impacted world regions differentially. Whereas some regions still record tens of thousands of new infections daily, other regions have contained the virus. What explains these striking regional differences? We advance a cultural psychological perspective on mask usage, a precautionary measure vital for curbing the pandemic. Four large-scale studies provide evidence that collectivism (versus individualism) positively predicts mask usage—both within the United States and across the world. Analyzing a dataset of all 3,141 counties of the 50 US states (based on 248,941 individuals), Study 1a revealed that mask usage was higher in more collectivistic US states. Study 1b replicated this finding in another dataset of 16,737 individuals in the 50 US states. Analyzing a dataset of 367,109 individuals in 29 countries, Study 2 revealed that mask usage was higher in more collectivistic countries. Study 3 replicated this finding in a dataset of 277,219 Facebook users in 67 countries. The link between collectivism and mask usage was robust to a host of control variables, including cultural tightness–looseness, political affiliation, demographics, population density, socioeconomic indicators, universal health coverage, government response stringency, and time. Our research suggests that culture fundamentally shapes how people respond to crises like the COVID-19 pandemic. Understanding cultural differences not only provides insight into the current pandemic, but also helps the world prepare for future crises.
I wish
Illustrations and short passages portray thirty-three individual men, women, and children whose wishes range from simply wanting never to blush to imagined feats of heroism.
Developmental Differences in Infants' Fairness Expectations From 6 to 15 Months of Age
The present research investigated the developmental trajectory of infants' fairness expectations from 6 to 15 months of age (N = 150). Findings revealed a developmental transition in infants' fairness expectations between 6 and 12 months, as indicated by enhanced visual attention to unfair outcomes of resource distribution events (a 3:1 distribution) relative to fair outcomes (a 2:2 distribution). The onset of naturalistic sharing behavior predicted infants' fairness expectations at transitional ages. Beyond this period of developmental transition, the presence of siblings and infants' prompted giving behavior predicted individual differences in infants' fairness concerns. These results provide evidence for the role of experience in the acquisition of fairness expectations and reveal early individual differences in such expectations.
The little pea
A little pea in a garden wants to be different from all the other peas, even though all the other peas laugh at him.
Large-scale analysis of test–retest reliabilities of self-regulation measures
The ability to regulate behavior in service of long-term goals is a widely studied psychological construct known as self-regulation. This wide interest is in part due to the putative relations between self-regulation and a range of real-world behaviors. Self-regulation is generally viewed as a trait, and individual differences are quantified using a diverse set of measures, including self-report surveys and behavioral tasks. Accurate characterization of individual differences requires measurement reliability, a property frequently characterized in self-report surveys, but rarely assessed in behavioral tasks. We remedy this gap by (i) providing a comprehensive literature review on an extensive set of self-regulation measures and (ii) empirically evaluating test–retest reliability of this battery in a new sample. We find that dependent variables (DVs) from self-report surveys of self-regulation have high test–retest reliability, while DVs derived from behavioral tasks do not. This holds both in the literature and in our sample, although the test–retest reliability estimates in the literature are highly variable. We confirm that this is due to differences in between-subject variability. We also compare different types of task DVs (e.g., model parameters vs. raw response times) in their suitability as individual difference DVs, finding that certain model parameters are as stable as raw DVs. Our results provide greater psychometric footing for the study of self-regulation and provide guidance for future studies of individual differences in this domain.
The art lesson
Having learned to be creative in drawing pictures at home, young Tommy is dismayed when he goes to school and finds the art lesson there much more regimented.
Task-free MRI predicts individual differences in brain activity during task performance
When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.