System:
You are an expert in research tasked with generating detailed prompts for various aspects of academic research papers. Each task involves creating a specific type of prompt based on the provided information. Here are the definitions of each part you will work with:

- Context: The status quo of related literature or reality which motivated this study. This could normally be a problem, a research question, or a research gap that has not been successfully addressed by previous work. This is anything that happened before this study.
- Key Idea: The main intellectual merit of this paper, often in comparison to the context. This could normally be a novel idea or solution proposed in this paper that distinguishes it from what's already done in literature. This is proposed in this study.
- Method: The specific research method that investigates and validates the key idea. This could be an experimental setup, a theoretical framework, or other necessary methodology to implement and/or evaluate the key idea. This is performed in this study.
- Outcome: The factual statement about the study output. This could be the experiment results and any other measurable outcome that has occurred. It marks whether the key hypothesis is testified or not. This is produced in this study.
- Projected Impact: The author-anticipated impact of the work on the field, and potential further research identified by the author that may improve or extend this study. This is anything being anticipated but has not happened yet.

Based on the context: 'A college degree is a key pathway to economic mobility for low-income students.', the key idea: 'Intensive advising in high school and college increases bachelor’s degree attainment primarily by improving the quality of initial college enrollment, suggesting a shift from affordability-only approaches to strategies targeting college choice.', the method: 'A multisite randomized controlled trial combined with administrative and survey data, leveraging unique preadvising college preference data and causal forest methods to assess mechanisms and treatment effects.', and the outcome: 'Intensive advising significantly increases bachelor’s degree attainment among lower-income students, with gains largely attributable to improvements in initial enrollment quality.', suggest the projected impact for this research. Output only the impact without explanation.

Strategies that target college choice may be more effective and efficient for increasing degree attainment than policies focused solely on affordability.


Based on the context: 'It has been challenging to isolate the component of homeowners’ moving decisions directly attributable to neighbors’ racial identities when studying neighborhood choice and racial change.', the key idea: 'A novel nearest-neighbor design contrasts move rates for homeowners who receive a new different-race neighbor immediately next-door versus slightly farther away on the same block to isolate preferences attributable to neighbor identity.', the method: 'The study measures move rates under the nearest-neighbor design and assesses robustness with additional controls such as income and alternative research designs.', and the outcome: 'Both Black and White homeowners are more likely to move after receiving a new different-race neighbor, with responses showing heterogeneity especially associated with housing density; findings are robust to controls and alternative designs.', suggest the projected impact for this research. Output only the impact without explanation.

The results have implications for understanding contemporary neighborhood racial change and the prospects for maintaining stable, integrated neighborhoods.


Based on the context: 'Cross-country differences in minimum wages and payroll taxes are common and may affect competition in labor-intensive trade, but the magnitude of these effects has been unclear.', the key idea: 'Labor market regulations materially shape trade competition in labor-intensive services, making export competitiveness partly dependent on domestic labor policies.', the method: 'The study exploits data from a large European trade program where firms from different countries supply labor services at the same location under differing payroll taxes and minimum wage rules, using country case studies and model-consistent gravity estimates to analyze responses to tax and regulatory reforms.', and the outcome: 'Country case studies and gravity estimates show large trade responses to labor cost changes, with the elasticity of trade in services to labor costs larger than one.', suggest the projected impact for this research. Output only the impact without explanation.

Absent regulatory and fiscal harmonization, domestic labor market policies will affect export competitiveness, informing debates on harmonization and policy design.


Based on the context: 'Instrumental variables analysis relies on assumptions like instrumental validity and additive separability, and there is concern about robustness when these assumptions fail.', the key idea: 'The paper establishes a trade-off in additive instrumental variables models: robustness to failures of instrumental validity or additive separability increases with stronger a priori structural restrictions, reducing flexibility.', the method: 'The study provides theoretical analysis, discusses implications for empirical practice, and includes a numerical study calibrated on real-world data.', and the outcome: 'It shows that robustness depends on the strength of a priori restrictions on the outcome–treatment relationship and demonstrates this with a calibrated numerical example.', suggest the projected impact for this research. Output only the impact without explanation.

The findings aim to guide empirical practice in IV by clarifying how modeling restrictions affect robustness, informing instrument choice and specification decisions.


Based on the context: 'Labor markets with asymmetric information create adverse selection, benefiting firms that can identify talent, especially in professions where performance is publicly observable.', the key idea: 'An informed intermediary exploits its information advantage by threatening to fire agents to expose them to undervaluation and later churning well-performing but less-skilled agents as track records erode its advantage, shaping wages and career choices through reputation-building incentives.', the method: 'A theoretical analysis models intermediated adverse selection with publicly observable performance, studying dynamic interactions among intermediary information advantages, firing/churning strategies, agent reputation formation, and wage setting.', and the outcome: 'The intermediary's accelerated reduction in information advantage boosts profits because retained agents accept below-reservation wages to build reputation faster; agents prefer starting careers with an intermediary since the gains from faster reputation building outweigh expropriation costs.', suggest the projected impact for this research. Output only the impact without explanation.

The analysis is applicable to professions where talent is critical and performance is publicly observable.


Based on the context: 'Software has become a disruptive technology and a key asset to price in the digital economy, with firms primarily valued for software growing from 2% to 13% of market share between 1996 and 2023.', the key idea: 'Persistent anomalies in growth forecasts and stock returns for software companies are interpreted as evidence of Bayesian investors gradually learning about software’s increasing importance, leading to deviations from rational expectations.', the method: 'Empirical documentation of anomalies by examining growth forecasts and stock returns of software companies over multiple decades to assess deviations from rational expectations and consistency with Bayesian learning.', and the outcome: 'The study finds persistent anomalies in growth forecasts and stock returns for software firms, indicating significant deviations from rational expectations over multiple decades and consistency with gradual investor learning.', suggest the projected impact for this research. Output only the impact without explanation.

The findings highlight that markets can be very slow to discern fundamental shifts from transient shocks in noisy data, informing how software should be priced and studied in asset pricing and corporate finance.


Based on the context: 'Saudi Arabia lifted the women's driving ban, raising questions about its impact on women's employment and autonomy.', the key idea: 'A field experiment randomizes access to rationed driver's training spaces to causally estimate how driving access affects women's employment and purchasing autonomy, including heterogeneity across subgroups.', the method: 'Randomized allocation of driver's training slots, with outcomes measured on employment likelihood and ability to make purchases without family permission, and analysis of heterogeneous treatment effects.', and the outcome: 'Treated women are 41% more likely to be employed and 19% less likely to be able to make purchases without family permission, with divergent effects concentrated in distinct subgroups.', suggest the projected impact for this research. Output only the impact without explanation.

Findings suggest intrahousehold responses can counteract legal gains in women's freedoms, indicating the need for policies that address household dynamics; N/A for specific future research directions.


Based on the context: 'In low-income countries, labor market power and employer concentration affect wage-setting, and self-employment is prevalent with implications for industrial development.', the key idea: 'Self-employment shapes labor market power by increasing the elasticity of wage labor supply in oligopsonistic markets, potentially weakening employer wage-setting power and implying that policies reducing self-employment could backfire.', the method: 'Empirical analysis using Peruvian data to relate employer concentration, self-employment prevalence, and wage-setting power, complemented by a general equilibrium model of oligopsonistic labor markets.', and the outcome: 'Wage-setting power rises with employer concentration but less so where self-employment is more prevalent; the model shows that self-employment raises wage labor supply elasticity, weakening employer market power, and that policies expanding wage employment and reducing self-employment may unintentionally strengthen labor market power.', suggest the projected impact for this research. Output only the impact without explanation.

The results inform industrial development policy by highlighting that procompetitive efforts to expand wage employment could undermine their objectives in settings with significant self-employment.


Based on the context: 'Predictable uninformed cash flows such as dividend payments are announced weeks in advance, raising the question of whether such flows forecast aggregate market returns.', the key idea: 'Predictable buying pressure from dividend payments is used to forecast value-weighted aggregate market stock returns, arguing that market-wide price pressure arises from flows.', the method: 'Empirical analysis relates market returns to the timing of dividend payment days, compares return outcomes across payment-day quintiles, examines international markets, conditions on reinvestment intensity and market liquidity, and estimates a market-level price multiplier.', and the outcome: 'Top-quintile payment days have market returns four times higher than the lowest, the effect holds internationally, is stronger when reinvestment is high and market liquidity is low, and the estimated market-level price multiplier is 1.9.', suggest the projected impact for this research. Output only the impact without explanation.

The findings suggest price pressure is a widespread result of flows rather than a financial market anomaly.


Based on the context: 'Populist narratives frequently depict intellectual elites as conspiring against them, and existing work has left several features of populism and its effects on political accountability unexplained.', the key idea: 'Populism is modeled as the dissemination of a false 'alternative reality' that discredits the elite's truthful message and reduces accountability, with conspiratorial elements endogenously chosen to better resist evidence.', the method: 'A theoretical model analyzes voters' receptiveness to an alternative reality, the impact of elite criticism on support for populists, and the populists' policy choices to leverage or strengthen beliefs in the alternative reality.', and the outcome: 'When enough voters are receptive, the alternative reality reduces political accountability; elite criticism increases receptive voters' support for the populist; alternative realities become endogenously conspiratorial; and populists enact harmful policies that may disproportionately harm the non-elite.', suggest the projected impact for this research. Output only the impact without explanation.

The results are claimed to explain previously unexplained facts about populism.


Based on the context: 'Incomplete market integration in major U.S. electricity markets creates allocative inefficiencies, and accelerating transmission investment is seen as a way to reduce total costs and improve renewable integration; incumbents may have the power to block reforms.', the key idea: 'Quantify static allocative inefficiencies from incomplete market integration and analyze firm-level revenue impacts to reveal incumbents’ incentives that could impede transmission expansion and market integration.', the method: 'Empirical documentation of inefficiencies over time in two major U.S. electricity markets, coupled with counterfactual estimation of firm-level net revenue changes under an integrated market.', and the outcome: 'Allocative inefficiencies have risen over time and totaled $2 billion in 2022; four firms would have experienced a collective $1.3 billion drop in net revenues in 2022 under market integration, with reports of some incumbents blocking transmission projects.', suggest the projected impact for this research. Output only the impact without explanation.

Findings support policies that accelerate transmission investment and market integration and underscore the need to address incumbent incentives in regulatory reforms to enhance efficiency and renewable integration.


Based on the context: 'Unemployment insurance take-up involves worker claims and employer appeals, making the employer's role a key factor in program targeting.', the key idea: 'Quantify employer effects on UI claiming and appeals and examine their negative correlation to understand deterrence and income gradients in take-up.', the method: 'Quantitative analysis estimating employer-specific effects on claiming and appeals and assessing correlations, alongside comparisons of claim and appeal rates across wage groups.', and the outcome: 'Employer effects on UI claiming and appeals are substantial and negatively correlated, consistent with appeals deterring claims. Low-wage workers are less likely to claim and more likely to have claims appealed than median-wage workers; employer effects help explain these income gradients, and the main source of targeting error is that eligible workers do not claim.', suggest the projected impact for this research. Output only the impact without explanation.

Equalizing employer effects on claiming would increase the progressivity of unemployment insurance.


Based on the context: 'There is an open question whether public sector organizations, especially in low-income countries, can improve worker performance by investing in mission motivation.', the key idea: 'Training designed to strengthen workers' mission motivation is proposed as a strategy to boost public sector performance.', the method: 'A randomized field experiment with community health workers in Pakistan evaluates the impact of mission-motivation training on performance across core monthly household visits and other tasks, and on child health outcomes.', and the outcome: 'Mission-motivation training increased workers’ performance in monthly household visits and in multiple tasks during and outside these visits, and led to improved child health outcomes in served communities.', suggest the projected impact for this research. Output only the impact without explanation.

Promoting organizational missions is highlighted as a promising approach to enhancing public sector performance in low-income settings.


Based on the context: 'The study investigates how expectations about long-run home price growth shape household spending decisions.', the key idea: 'Expectations are exogenously varied by providing different expert home price forecasts to respondents, enabling identification of spending responses and comparison between homeowners and renters.', the method: 'A field experiment with US households manipulates expectations via randomized expert forecasts in a survey and measures subsequent spending using rich home-scanner data.', and the outcome: 'Homeowners’ spending is inelastic to home price expectations, whereas renters reduce spending when expecting higher home price growth; these patterns are consistent with positive wealth effects for owners and negative income effects from higher future housing costs for both groups.', suggest the projected impact for this research. Output only the impact without explanation.

The findings highlight the consequences of asset price growth and long-term expectations for household behavior.


Based on the context: 'Children often spend years in foster care, with bureaucratic hurdles unnecessarily prolonging stays; Chile introduced the Mi Abogado program to enhance legal aid and accelerate family reunification.', the key idea: 'The study evaluates the impact of enhanced legal aid for foster children via the Mi Abogado program, leveraging a government-randomized rollout to assess effects on child well-being.', the method: 'A randomized trial of the program’s introduction for children in institutions, analyzed using registry data to measure outcomes including foster care duration, maltreatment, placements, criminal justice involvement, and school attendance.', and the outcome: 'Program exposure significantly reduced the duration of foster care without increasing subsequent maltreatment or placements, decreased criminal justice involvement, and improved school attendance.', suggest the projected impact for this research. Output only the impact without explanation.

Strengthening foster care services through enhanced legal aid may cost-effectively improve child well-being.


Based on the context: 'The paper reviews prior work on comparative development, colonialism, institutional change, and innovation, emphasizing how periods of disruption can amplify small differences in affecting prosperity and institutional trajectories.', the key idea: 'A simple framework centered on a utility-technology possibilities frontier is introduced to organize how institutions, market structures, norms, and ideologies influence resource distribution and technological choices.', the method: 'A theoretical framework is developed to formalize movements along and shifts of the utility-technology frontier and to connect insights from research on institutions and technology.', and the outcome: 'The framework highlights mechanisms behind institutional persistence and change, conceptualizes amplified effects of small differences during disruptions, and suggests parallels across European colonialism, 19th-century industrial technologies, and contemporary AI-related decisions.', suggest the projected impact for this research. Output only the impact without explanation.

The framework is anticipated to guide analyses of comparative development and inform decisions about the use, adoption, and development of AI.


Based on the context: 'Consumers often continue to pay for subscriptions they no longer value, creating a potential benefit for firms that sell subscriptions.', the key idea: 'Leverage payment card replacement episodes and stylized models of consumer inertia (inattention and switching costs) to identify and quantify how cancellation frictions elevate subscription revenues, and assess regulatory remedies.', the method: 'Analyze comprehensive data from a large payment card network to compare cancellation rates in months when cards are replaced (requiring active renewal), and estimate two stylized inertia models to quantify revenue effects and simulate regulatory impacts.', and the outcome: 'Card replacement months are associated with much higher cancellation rates, and estimated cancellation frictions roughly double seller revenues on average, holding fixed initial subscribers.', suggest the projected impact for this research. Output only the impact without explanation.

The findings guide evaluation of regulatory remedies aimed at reducing cancellation frictions in subscription markets.


Based on the context: 'Data-driven innovation in socially impactful digital products faces challenges in measuring and improving social impact, particularly when designing and analyzing complex experiments.', the key idea: 'The paper offers an economic perspective on the innovation process, positioning economists as designers who leverage complex experiments and economic tools to identify problems, build theory, define measurable goals, analyze data, and estimate counterfactuals.', the method: 'A conceptual synthesis and survey that outlines how economic tools apply at each stage of the innovation process and reviews recently developed tools for designing and analyzing data from complex experiments.', and the outcome: 'The paper highlights specific contributions of economics—problem identification, theoretical framework development, translating goals into measurable outcomes, historical data analysis, and counterfactual estimation—and surveys tools to address experimental design and analysis challenges.', suggest the projected impact for this research. Output only the impact without explanation.

The framework and surveyed tools are intended to improve the design and evaluation of data-driven digital products with social impact and guide future research on complex experimental methodologies.


Based on the context: 'Application hassles ('ordeals') are used to limit public program enrollment, and insurance markets commonly feature adverse selection.', the key idea: 'Examining a minor ordeal created by removing health insurance auto-enrollment, the study argues that in selection markets adverse selection undermines the standard rationale for ordeals that aim to exclude low-value individuals.', the method: 'An empirical analysis of the removal of an auto-enrollment policy that added an extra enrollment step, combined with a simple model to assess how adverse selection interacts with ordeals.', and the outcome: 'The minor ordeal reduced enrollment by 33% and disproportionately excluded young, healthy, and economically disadvantaged individuals; the model shows that adverse selection weakens ordeals’ ability to target inefficiency because low-value individuals are also low-cost.', suggest the projected impact for this research. Output only the impact without explanation.

The analysis illustrates that ordeals targeting is unlikely to work well in selection markets.


Based on the context: 'The study addresses the challenge of achieving robust behavioral change among disadvantaged adolescents in school settings.', the key idea: 'A behavioral targeting program grants status and leverages self-persuasion by enlisting socially connected senior middle school students with high emotional intelligence as student-teachers to deliver a curriculum to their junior peers.', the method: 'The intervention recruits these student-teachers to deliver a curriculum and evaluates effects on disciplinary incidents, antisocial behavior, the social environment, and admissions to selective high schools for student-teachers and their friendship networks.', and the outcome: 'The program empowered student-teachers and improved their social environment; it reduced disciplinary incidents and antisocial behavior among student-teachers and their friendship networks; it significantly increased student-teachers' likelihood of admission to selective high schools.', suggest the projected impact for this research. Output only the impact without explanation.

The approach offers a cost-effective way to help disadvantaged adolescents escape neighborhood disadvantages.


Based on the context: 'Debate over whether central banks should keep inflation targets fixed and the presence of persistent private information at the central bank motivate a study of target design under asymmetric information.', the key idea: 'A dynamic inflation target mechanism is proposed that delegates to the central bank the authority to adjust the target’s level and flexibility one period in advance, implementing the full-information commitment allocation.', the method: 'A theoretical dynamic mechanism design framework between a government and a central bank with persistent private information about structural shocks, where firms form inflation expectations based on the central bank’s reports.', and the outcome: 'A dynamic inflation target can implement the full-information commitment allocation, and a declining natural interest rate versus a flattening Phillips curve imply opposite optimal adjustments to the target.', suggest the projected impact for this research. Output only the impact without explanation.

The results provide guidance for practical policy decisions on how to design and adjust inflation targets.


Based on the context: 'Automated content moderation requires accurate, context-sensitive hate speech evaluation, and multimodal large language models could improve this by integrating contextual information, necessitating assessment of their performance and alignment with human judgement.', the key idea: 'The study uses conjoint experiments to systematically audit MLLMs' context-sensitive hate speech evaluations by varying post attributes and benchmarking model decisions against human judgements, including tests of prompting and sensitivity to visual identity cues.', the method: 'Models were given a hate speech policy and evaluated simulated social media posts that varied in slur usage, user demographics and other attributes; their decisions were benchmarked against judgements from 1,854 human participants, with further analyses of prompting effects and responsiveness to visual identity cues.', and the outcome: 'Larger, more advanced models made context-sensitive evaluations closely aligned with human judgement; pervasive demographic and lexical biases persisted, particularly among smaller models; prompting amplified context sensitivity but did not eliminate biases, and some models were especially responsive to visual identity cues.', suggest the projected impact for this research. Output only the impact without explanation.

The findings underscore the benefits and risks of deploying MLLMs for content moderation and suggest conjoint experiments as a useful approach for auditing AI in complex, context-dependent applications.


Based on the context: 'Comparing information structures between deep neural networks and the human brain is a key approach, with prior work showing vision–language models (e.g., CLIP) align better with ventral occipitotemporal cortex activity than vision-only models, but interpretation is limited by the black-box nature of DNNs.', the key idea: 'Combine model–brain fitness analyses with human brain-lesion data to causally test how disrupting communication between visual and language systems affects the ability of vision–language models to explain visual cortex activity, thereby probing language modulation of human vision.', the method: 'Across four datasets, evaluate model–brain correspondence in VOTC for CLIP versus label-supervised (ResNet) and unsupervised (MoCo) models, assess lateralization, and analyze 33 stroke patients by correlating white matter integrity between VOTC and the left angular gyrus with model–brain similarity.', and the outcome: 'CLIP consistently captured unique variance in VOTC neural representations relative to ResNet and MoCo, with a left-lateralized advantage; reduced visual–language white matter integrity was associated with decreased CLIP–brain correspondence and increased MoCo–brain correspondence.', suggest the projected impact for this research. Output only the impact without explanation.

Findings support integrating language modulation into neurocognitive models of human vision and demonstrate that leveraging specific brain lesions is a promising framework for evaluating and developing brain-like computational models.


Based on the context: 'Climate-related disasters like wildfires and floods pose escalating risks, yet motivating individuals to adopt protective measures is a persistent challenge due to barriers such as psychological distance.', the key idea: 'A behavioral intervention personalizes climate risk communications by integrating proximal cues (e.g., recipients' suburbs) to reduce psychological distance and foster place attachment.', the method: 'A pre-registered randomized field experiment with 12,985 Australian homeowners in wildfire-prone areas compared localized, place-cued emails to generic communications and measured click-throughs and information-seeking about wildfire preparedness.', and the outcome: 'Localized messages doubled the likelihood of seeking further preparedness information compared to generic messages (odds ratio 2.03, 95% CI 1.33–3.16), increasing click-throughs and engagement.', suggest the projected impact for this research. Output only the impact without explanation.

The intervention offers a scalable, low-cost approach to enhance disaster preparedness and provides guidance for leveraging behavioral science to mitigate impacts of climate-related disasters.


Based on the context: 'Human language exhibits systematic structure with words and phrases, motivating an explanation of how such structure arises and its relation to general cognitive constraints.', the key idea: 'Languages can be understood as codes that minimize predictive information, leading to systematic and local expression of approximately independent features akin to words and phrases.', the method: 'The study uses simulations to examine codes that minimize predictive information and analyzes cross-linguistic text corpora to compare predictive information against baselines at phonology, morphology, syntax, and lexical semantics.', and the outcome: 'Simulations show that minimizing predictive information yields message groupings into approximately independent features expressed locally, and empirical analyses find that human languages have low predictive information compared with baselines across multiple linguistic levels.', suggest the projected impact for this research. Output only the impact without explanation.

The findings establish a link between the statistical and algebraic structure of language and reinforce the view that language structures are shaped by communication under general cognitive constraints.


Based on the context: 'Humans possess culturally dependent repertoires that exceed individual innovation capacity, and it is unclear whether non-human animals require social learning to achieve adult-like breadths of knowledge by key developmental milestones or can rely primarily on independent exploration.', the key idea: 'The study proposes that orangutan diet repertoires are culturally dependent and that social learning is critical to drive diet development beyond individual exploratory potentials.', the method: 'An empirically validated agent-based model was built from an extensive dataset of wild orangutan behavior to simulate immature diet development under conditions with and without multiple forms of social learning.', and the outcome: 'In the model, diets reached adult-like breadths only when immatures benefited from multiple social learning mechanisms, and social learning was necessary for achieving adult-like breadths by the age of independence from mothers.', suggest the projected impact for this research. Output only the impact without explanation.

The findings suggest orangutan diets are culturally dependent and point to new avenues for investigating how cultural repertoires are built in hominids and other species.


Based on the context: 'Reinforcement learning algorithms have been successful in explaining reward-based learning, including instrumental learning in contextual bandit tasks and accounting for brain signal variance, but human reward learning involves multiple processes like memory and choice perseveration that can be misattributed to RL.', the key idea: 'The study examines how much human reward-based learning is truly supported by RL computations and proposes a dual-process account combining a fast working-memory-based mechanism with a slower habit-like associative mechanism.', the method: 'The author reanalyzes and conducts computational modeling across seven datasets (n=594) from diverse samples in an instrumental learning context designed to factor out other processes.', and the outcome: 'Reward-based learning behavior is best explained by the joint influence of a fast working-memory process and a slower habit-like associative process, neither of which aligns with a standard RL algorithm on its own.', suggest the projected impact for this research. Output only the impact without explanation.

The results challenge conventional interpretations of RL algorithms as capturing meaningful cognitive processes across brain and behavior, prompting reconsideration of how RL is used to model human learning.


Based on the context: 'There is growing interest in how individuals adjust goals when encountering striving difficulties, but research is fragmented across theoretical perspectives and life domains.', the key idea: 'A comprehensive meta-analytic review introduces a conceptual model that categorizes and maps antecedents and outcomes of goal disengagement, reengagement, and goal-striving flexibility to consolidate the field.', the method: 'A systematic search across multiple databases (last updated May 2025) identified eligible studies on predictors and outcomes of goal adjustment; 1,421 effect sizes from 235 studies were categorized and analyzed using random-effects meta-analyses, with study quality assessed using QualSyst.', and the outcome: 'The review found associations between multiple antecedent categories and goal disengagement, reengagement and flexibility, and between these aspects of goal adjustment and wellbeing, functional, and goal-related outcomes; each aspect is predicted by unique combinations of antecedents and predicts distinct outcomes. The overall evidence quality was judged low to moderate due to reliance on cross-sectional studies, risk of publication bias, and high heterogeneity.', suggest the projected impact for this research. Output only the impact without explanation.

The conceptual model consolidates the literature and offers a roadmap for more systematic investigation of goal adjustment going forward.


Based on the context: 'Brain-wide association studies have focused on inter-regional coupling, while intra-regional spontaneous dynamics remain largely unexplored despite their importance for understanding inter-individual differences.', the key idea: 'Characterizing intra-regional resting-state haemodynamic dynamics with rich time-series features to derive stable, individual-specific 'barcodes' that capture inter-individual variation and enable generalizable brain–behaviour associations beyond traditional connectivity measures.', the method: 'Analyzed four neuroimaging cohorts (ages 8–82 years; N=30,148), extracted ~5,000 time-series features from resting-state signals across 271 brain regions, identified a reliable subset as individual barcodes, and tested associations between barcode dimensions and behavioural traits (substance use, general cognitive abilities) across datasets and age groups.', and the outcome: 'Stable individual-specific barcodes were identified across datasets; nonlinear autocorrelations in unimodal regions were linked to substance use traits and random walk dynamics in higher-order networks to general cognitive abilities; these associations generalized across life stages and populations, with age-specific variation for substance use and consistent patterns for cognition.', suggest the projected impact for this research. Output only the impact without explanation.

The results highlight intra-regional dynamics as a foundation for large-scale, generalizable brain-wide association studies and encourage broader use of regional temporal barcodes to link brain activity to behaviour across populations and life stages.


Based on the context: 'Young adults face rising loneliness and mental health challenges, motivating research on barriers to social connection.', the key idea: 'The study introduces an 'empathy perception gap'—people underestimate others’ empathy—and proposes bridging this gap by presenting peers’ self-reported empathy and nudging social risk-taking to foster connection.', the method: 'A longitudinal study of 5,192 undergraduates assessed perceived peer empathy and well-being, complemented by two field experiments that shared data on peers’ empathy and provided behavioral nudges encouraging social risk-taking.', and the outcome: 'Perceiving peers as empathic was associated with better current and future well-being; students systematically underestimated peers’ empathy, and lower perceived empathy predicted reduced social risk-taking and increased isolation. Interventions reduced the perception gap, increased social behaviors, and expanded social networks months later.', suggest the projected impact for this research. Output only the impact without explanation.

The findings indicate a promising, scalable approach to cultivating social well-being by simply sharing information about peers’ empathy.


Based on the context: 'Emotional events are vividly remembered and emotions involve brain-wide network interactions, but it is unclear whether and how whole-brain dynamics contribute to memory encoding.', the key idea: 'Emotional arousal enhances memory encoding by strengthening functional integration across large-scale brain networks, with an integrated brain state (increased cohesion across functional modules) proposed as the mechanism linking arousal to recall fidelity.', the method: 'Functional MRI, graph theory, text analyses, and pupillometry were combined in a naturalistic paradigm where participants perceived narratives and later recalled them in their own words, analyzing three independent datasets to test associations and mediation among arousal, network integration, and memory fidelity.', and the outcome: 'Emotionally arousing narrative moments were associated with increased functional integration across brain networks, which predicted subsequent recall fidelity, and network integration mediated the effect of arousal on recall, supported by consistent within- and between-network interactions across datasets.', suggest the projected impact for this research. Output only the impact without explanation.

The findings are expected to advance a cross-level understanding of emotional memory by bridging large-scale brain network dynamics, affective states, and ongoing cognition.


Based on the context: 'Psychometric network models are widely used to explore multivariate data, with edges interpreted as evidence of conditional associations, yet the statistical support for these edges is seldom evaluated.', the key idea: 'Quantify the statistical evidence for network edges using a Bayesian approach (inclusion Bayes factors) to assess how strongly reported associations are supported.', the method: 'Reanalysis of 293 networks from 126 published papers using inclusion Bayes factors (BF10) for each edge, categorizing evidence strength and examining how sample size relates to robustness.', and the outcome: 'About one-third of edges showed inconclusive evidence (1/3 < BF10 < 3), roughly half showed weak evidence (BF10 > 3 or BF10 < 1/3), and fewer than 20% were strongly supported (BF10 > 10 or BF10 < 1/10); larger sample sizes yielded more robust networks.', suggest the projected impact for this research. Output only the impact without explanation.

The results call for caution when interpreting individual edges in psychometric networks and encourage more rigorous evaluation of statistical evidence in future research.


Based on the context: 'Climate change impacts vary across locations, raising the possibility that migration from high-risk to lower-risk areas could reduce future damages; assessing whether such migration is already occurring can inform expectations about future responses.', the key idea: 'The study examines whether hurricanes and tropical storms trigger county-level outmigration in the USA and whether migration reduces exposure, leveraging comprehensive storm path data and differentiating responses by storm destructiveness and local economic activity.', the method: 'An empirical analysis uses data on the paths of all Atlantic basin hurricanes and tropical storms from 1992 to 2017 to relate county-level outmigration to storm exposure, track population-weighted exposure over time, and compare responses by storm severity and economic activity.', and the outcome: 'On average, storms are not followed by outmigration and population-weighted exposure to storms increased over 1992–2017; very destructive storms lead to outmigration, often to other high-risk counties; counties with high economic activity experience net in-migration after a storm, indicating that benefits of high-risk areas outweigh incentives to relocate to reduce future exposure.', suggest the projected impact for this research. Output only the impact without explanation.

The findings inform understanding of how migration may respond to climate change and help anticipate the extent to which migration will mitigate future climate damages.


Based on the context: 'Prior research on seriation suggests children struggle to apply algorithmic strategies in simple sorting tasks, despite efficient algorithms enhancing problem-solving.', the key idea: 'Children can spontaneously discover and apply efficient sorting algorithms when faced with a more demanding variant of the task with hidden ranks, indicating greater competence than previously believed.', the method: 'Children completed a sorting task with animated bunnies whose heights were hidden behind a wall; their performance and strategies were analyzed across ages to identify spontaneous use of efficient algorithms.', and the outcome: 'Children performed far above chance, independently discovered efficient algorithms such as selection sort and shaker sort, and older children sorted more effectively and used efficient strategies more frequently.', suggest the projected impact for this research. Output only the impact without explanation.

The findings suggest a reassessment of children's capacity for strategic, algorithmic problem-solving and highlight developmental progress in strategic thinking and problem-solving abilities.


Based on the context: 'Addressing societal challenges requires unrelated individuals to reduce conflict and coordinate actions, yet the role of honour—often studied in relation to conflict—in competition and cooperation is underexplored.', the key idea: 'The study examines how perceived normative honour values and personally endorsed honour values predict competition and cooperation, framing honour as a cultural logic with distinct forms.', the method: 'A preregistered online experiment with 3,371 participants from 13 societies elicited incentivized competition decisions in a contest game and cooperation decisions in a step-level public goods game, alongside measures of perceived societal honour norms and personal honour endorsements.', and the outcome: 'Perceived normative honour values were associated with greater competition and greater cooperation at both societal and individual levels; endorsing defence of family reputation predicted greater coordination, while endorsing self-promotion and retaliation predicted weaker coordination.', suggest the projected impact for this research. Output only the impact without explanation.

The findings highlight honour, in its different forms, as a cultural logic shaping competition and cooperation across societies.


Based on the context: 'Economic games integrated with network science are used to study social behavior, but traditional models and experiments restrict players from taking different actions toward distinct social neighbors, limiting social networking agency.', the key idea: 'Introducing and manipulating social networking agency—allowing individuals to tailor actions to each neighbor—to examine its effects on cooperation, trust, and fairness in economic games.', the method: 'An experimental paradigm that varies network agency was applied to the prisoner’s dilemma, trust game, and ultimatum game (N=735 each), comparing groups with greater agency to control groups on prosocial behaviors, wealth, and inequality.', and the outcome: 'Granting greater network agency increased cooperation, trust, and fairness across all three games and led to higher wealth and lower inequality relative to control groups.', suggest the projected impact for this research. Output only the impact without explanation.

Incorporating social networking agency into experimental designs is expected to better capture the prosocial potential of human behavior.


Based on the context: 'Social norms messaging is widely used as a cost-effective strategy to change health behaviors, but its overall effectiveness has not been comprehensively evaluated.', the key idea: 'A pre-registered, comprehensive systematic review and meta-analysis of randomized controlled trials assesses the effectiveness of social norms messaging on health behaviors, incorporating robust adjustments for publication bias and moderator analyses.', the method: 'Randomized controlled trials from developed countries targeting individuals aged 16+ were systematically identified across multiple databases; risk of bias was assessed with Cochrane RoB 2 by two reviewers; a random-effects meta-analysis standardized effects to Cohen’s d, evaluated heterogeneity with I², applied robust Bayesian meta-analysis to adjust for publication bias, and conducted moderator analyses by message type, delivery modality, health domain, and population.', and the outcome: 'Across 89 studies (n=85,759), social norms messaging showed a small pooled effect (d=0.1, 95% CI [0.09, 0.19], P<0.001) that disappeared after controlling for publication bias; moderator analyses revealed no significant differences by message type, modality, health domain, or population.', suggest the projected impact for this research. Output only the impact without explanation.

Findings suggest social norms messages are not effective at improving health behaviors once publication bias is accounted for, indicating that future public health efforts should prioritize alternative behavior-change approaches.


Based on the context: 'Low-socioeconomic-status and immigrant households benefit most from high-quality early childcare yet access it least, with large enrolment disparities in France; cognitive and behavioral barriers are suspected contributors.', the key idea: 'Reducing administrative burden and information costs through informational interventions and personalized support is proposed to address social inequalities in early childcare applications and access.', the method: 'A multi-arm randomized controlled trial with 1,849 households in France tested an information-only intervention versus personalized support aimed at alleviating administrative burdens, measuring effects on application and access rates.', and the outcome: 'The information-only treatment had minimal impact, while personalized support significantly eliminated SES and migration gaps in applications; despite higher application rates, impacts on access rates for low-SES and immigrant households were limited.', suggest the projected impact for this research. Output only the impact without explanation.

The study highlights the need for integrated strategies beyond information provision to promote equal opportunities in early childhood education by addressing key obstacles to access for low-SES and immigrant households.


Based on the context: 'School interventions aimed at improving adolescents’ general knowledge of vaccination are rare, despite their potential to reduce vaccine hesitancy.', the key idea: 'Two scalable school-based interventions—a set of ready-to-use pedagogical activities for teachers and a chatbot—are proposed to improve adolescents’ attitudes toward and knowledge of vaccination compared to the standard curriculum.', the method: 'A cluster-randomized trial with 8,589 French ninth graders from 399 schools compared the two interventions against the standard curriculum, measuring changes in attitudes toward vaccination (primary outcome) and knowledge.', and the outcome: 'Both interventions significantly improved attitudes (Pedagogical Activities: t398=2.99, P=0.003, β=0.094, 95% CI [0.032, 0.156]; Chatbot: t398=2.07, P=0.039, β=0.063, 95% CI [0.003, 0.124]) and knowledge (Pedagogical Activities: t398=3.23, P=0.0013, β=0.103, 95% CI [0.040, 0.165]; Chatbot: t398=2.23, P=0.027, β=0.070, 95% CI [0.008, 0.132]).', suggest the projected impact for this research. Output only the impact without explanation.

The interventions offer scalable ways to counter vaccine hesitancy among adolescents and have important public health implications by improving acceptance and understanding of vaccines.


Based on the context: 'Private hosting of refugees in Europe has increased during the Ukrainian displacement crisis, but its impact on refugee integration remains understudied.', the key idea: 'The study assesses the short- to medium-term effects of private hosting on multidimensional integration outcomes for Ukrainian refugees in Germany by leveraging a matching platform dataset.', the method: 'Using data from a large non-profit platform, the study compares integration outcomes of refugees matched with private hosts to those of observably similar applicants who were not matched (n=1,700), evaluating social, psychological, navigational, linguistic, economic, and political dimensions.', and the outcome: 'Private hosting led to significant improvements in social, psychological, and navigational integration, with no discernible effects on linguistic, economic, or political integration; the study provides causal evidence of these effects.', suggest the projected impact for this research. Output only the impact without explanation.

Findings suggest private hosting can complement traditional public asylum reception and housing systems and mobilize civil society to enhance refugee integration during humanitarian crises.


Based on the context: 'Traditional smoking cessation interventions have limited coverage, and while digital approaches show promise, their comparative efficacy across methodological frameworks and technology types is unclear.', the key idea: 'The study systematically compares digital smoking cessation interventions by methodology and technology type to determine which approaches are most effective relative to standard care.', the method: 'A frequentist random-effects network meta-analysis of 152 randomized controlled trials categorized interventions by methodology and technology type, with cross-matched subgroup and sensitivity analyses.', and the outcome: 'Personalized interventions improved cessation versus standard care (RR 1.86, 95% CI 1.54–2.24); group-customized interventions were more effective (RR 1.93, 95% CI 1.30–2.86) than standard digital interventions (RR 1.50, 95% CI 1.31–1.72); text message-based interventions were most effective (RR 1.63, 95% CI 1.38–1.92); middle-aged individuals benefited more than younger individuals; short- and medium-term programs outperformed long-term ones; sensitivity analyses supported these low-to-moderate findings, with limitations including methodological heterogeneity, potential bias, inconsistent definitions, and limited long-term follow-up.', suggest the projected impact for this research. Output only the impact without explanation.

The authors call for large-scale trials to assess long-term sustainability and population-specific responses, as well as standardization of methods and individual-level data integration.


Based on the context: 'Functional near-infrared spectroscopy (fNIRS) is sensitive to individual biophysical differences such as hair and skin characteristics, which can bias signal quality and disproportionately affect diverse populations.', the key idea: 'The study quantifies how hair properties, skin pigmentation, and other factors affect fNIRS signal quality and proposes practical recommendations to enhance inclusivity in fNIRS research.', the method: 'Signal quality was assessed in n=115 individuals while measuring hair properties, skin pigmentation, head size, sex, and age; the authors also developed a suggested metadata table and guidance for cap and optode configurations and hair management techniques.', and the outcome: 'Hair properties and skin pigmentation, along with head size, sex, and age, were found to impact fNIRS signal quality, and the study produced recommendations to optimize data collection across varied participants.', suggest the projected impact for this research. Output only the impact without explanation.

The recommendations aim to guide future hardware advances and methodological standards to overcome barriers to inclusivity in fNIRS studies.


Based on the context: 'Prior research has established that human mobility exhibits scale-free patterns and proposed models explaining these distributions, but it has not explicitly addressed how geographical constraints (landmasses, waterways, and built environment) structure mobility.', the key idea: 'The study separates the effect of geography from mobility choices by incorporating geography via the pair distribution function, revealing an underlying power-law behavior across five orders of magnitude and linking spatial settlement structure to mobility.', the method: 'Using millions of movement records, the authors apply physics-based models and integrate geography through the pair distribution function to encapsulate the structure of locations, thereby decoupling geographical layout from observed mobility choices.', and the outcome: 'Separating geography from mobility choices reveals a power law spanning five orders of magnitude and identifies an underlying pattern in movement independent of geographical layout, showing how the spatial distribution of human settlements shapes human mobility.', suggest the projected impact for this research. Output only the impact without explanation.

The approach is intended to bridge the gap between distance-based and opportunity-based models of human mobility.


Based on the context: 'Complementary, alternative and integrative medicine (CAIM) use is highly prevalent among autistic individuals, but the evidence for its effects remains uncertain.', the key idea: 'Conduct an umbrella review of meta-analyses on CAIM for autism across the lifespan and develop a web platform to standardize and disseminate the findings.', the method: 'Five databases were searched up to December 31, 2023 for systematic reviews with meta-analyses; independent pairs of investigators screened and extracted data; meta-analyses were reestimated using a consistent statistical approach, methodological quality was assessed with AMSTAR-2, and certainty of evidence was appraised using an algorithmic GRADE framework.', and the outcome: 'Fifty-three meta-analytic reports were identified, enabling 248 meta-analyses across 19 CAIMs; no high-quality evidence supports the efficacy of any CAIM for core or associated autism symptoms, with several showing promising but very low-quality evidence; safety is rarely evaluated; an interactive platform was launched (https://ebiact-database.com).', suggest the projected impact for this research. Output only the impact without explanation.

The findings underscore the need for rigorous evaluation of CAIM safety and efficacy in autism and provide a resource to support evidence-based consideration and guide future research.


Based on the context: 'There is a lack of large-scale studies examining cultural differences and generational trends in spousal correlations for psychiatric disorders, even though spousal trait similarity can affect prevalence, comorbidity, and bias genetic architecture estimates.', the key idea: 'A large-scale, cross-national and generational investigation assesses the consistency of spousal correlations across nine psychiatric disorders.', the method: 'Analyses of three national registries computed spousal trait correlations: Taiwan (five million spousal pairs), Denmark (571,534 pairs), and published Swedish results (707,263 pairs), with generational changes examined in Taiwan for cohorts born after the 1930s.', and the outcome: 'A majority of psychiatric disorders show consistent spousal correlations across nations and over generations, and spouses often share psychiatric disorders.', suggest the projected impact for this research. Output only the impact without explanation.

The consistency of spousal correlations suggests important effects on the population dynamics and inheritance of psychiatric disorders, with implications for prevalence, comorbidity, and genetic architecture estimation.


Based on the context: 'Systemic racism drives racial disparities in the US, but while structural and interpersonal racism are well characterized, cultural racism lacks a robust, validated measure.', the key idea: 'A theory-driven, empirical latent measure of cultural racism is developed using nine indicators to quantify this dimension of systemic racism.', the method: 'Confirmatory factor analysis on nine indicators defines the cultural racism factor, followed by analysis of CDC WONDER mortality data (2018–2021) to assess associations with all-cause mortality rates and life expectancy for Black and white adults.', and the outcome: 'Each unit increase in the cultural racism factor is associated with approximately 136 (95% CI: 90 to 182) additional all-cause deaths per 100,000 and about a one-year decline in life expectancy (−1; 95% CI: −2 to −1), with associations consistent across Black and white adults.', suggest the projected impact for this research. Output only the impact without explanation.

The measure is intended to advance research on racism and health and provide an empirical basis for efforts to address US health inequities.


Based on the context: 'Resistance to cognitive biases is a crucial component of rationality that affects judgement and decision-making, motivating a synthesis of educational debiasing efforts.', the key idea: 'A systematic review and meta-analysis quantifies the effectiveness of educational interventions in reducing cognitive biases among students, focusing on randomized controlled trials.', the method: 'A systematic review identified 54 randomized controlled trials (383 effect sizes; 10,941 participants) and a meta-analysis synthesized 160 effects from 41 studies; most interventions used cognitive strategies targeting biases (e.g., confirmation bias), and risk of bias and publication bias were assessed.', and the outcome: 'Educational interventions produced a small but statistically significant reduction in committing biases compared with controls (g = 0.26, 95% CI 0.14 to 0.39, P < 0.001); some biases (e.g., representativeness heuristic) were harder to overcome; included studies had unclear or high risk of bias and some risk of publication bias.', suggest the projected impact for this research. Output only the impact without explanation.

More research is needed to evaluate the transfer of learning to real-world decision-making and to identify which pedagogical approaches most effectively reduce cognitive biases.


Based on the context: 'As populations age globally, ensuring equitable access to essential services for older adults is increasingly important.', the key idea: 'A fairness index is introduced to compare revealed service accessibility between high-ageing and low-ageing Census Block Groups across health care, housing, and food.', the method: 'The study constructs a fairness index and analyzes datasets spanning diverse demographic and geographic contexts to assess revealed accessibility of key services for ageing populations across the USA, including comparisons between high-ageing and low-ageing areas and projections over time.', and the outcome: 'Ageing communities generally exhibit better accessibility, but the advantage is uneven and projected to decline; up to 70% of high-ageing areas in some states lack access to ageing-specific services, indicating substantial geographic disparities.', suggest the projected impact for this research. Output only the impact without explanation.

The findings inform urban planning and policy debates on equitable service provision for ageing populations and highlight the need for more equitable responses to demographic ageing.


Based on the context: 'It is unknown whether information from different sensory modalities is accumulated by distinct processes and whether these processes have separate decision criteria during multisensory detection.', the key idea: 'Auditory and visual evidence are accumulated in distinct processes that sub-additively co-activate a single, thresholded motor process during redundant detection.', the method: 'Two experiments (n=22; n=21) employed a paradigm tracing neural evidence accumulation via centro-parietal positivity, modeled alongside response time distributions; analyses included redundant and conjunctive audio-visual detection, joint neural–behavioral modeling, and a follow-up onset-asynchrony experiment.', and the outcome: 'Auditory and visual evidence were found to be accumulated in distinct processes, and cumulative evidence in the two modalities sub-additively co-activated a single motor process during redundant detection.', suggest the projected impact for this research. Output only the impact without explanation.

The findings address long-standing questions about information integration and accumulation in multisensory conditions.


Based on the context: 'Multiple overlapping socioeconomic vulnerabilities are associated with an increased burden of HIV and progression to AIDS among Brazilian women.', the key idea: 'The study assesses the intersectional effectiveness of the Programa Bolsa Família conditional cash transfer on reducing AIDS incidence and AIDS-related mortality among low-income daughters and mothers.', the method: 'Using a quasi-experimental impact evaluation design, the authors analyze a cohort of 12.3 million low-income Brazilian women (2007–2015) to estimate rate ratios for AIDS incidence and AIDS-related mortality associated with participation in PBF, stratified by intersecting vulnerabilities.', and the outcome: 'PBF was associated with reductions in AIDS incidence and mortality: daughters had RR 0.53 (incidence) and RR 0.45 (mortality); mothers had RR 0.58 (incidence) and RR 0.57 (mortality), with stronger effects among those with one or two intersecting vulnerabilities, notably brown/Black and extremely low income (RR 0.47), and the greatest effect in extremely low-income, brown/Black mothers with higher education (RR 0.44).', suggest the projected impact for this research. Output only the impact without explanation.

Conditional cash transfers could substantially reduce AIDS-related inequalities and help achieve AIDS-related Sustainable Development Goals, highlighting social protection’s role in addressing health inequalities.


Based on the context: 'Style is a major form of creative expression, yet prior work has focused on its social, political, and aesthetic significance rather than the cognitive and computational mechanisms underlying style perception.', the key idea: 'Style perception is characterized as a process that separates form from content, proposing that this capacity is grounded in psychological mechanisms that parse stylistic information independently of object identity.', the method: 'Ten experiments using classic psychophysical paradigms with both naturalistic images and synthetic stimuli, complemented by an object recognition model to capture human judgments of image similarity across different styles.', and the outcome: 'Experiments reveal perceptual tuning to stylistic information, representational constancy across stylistic variation, and mental rendering of novel styled objects; the object recognition model successfully captures human similarity judgments across styles.', suggest the projected impact for this research. Output only the impact without explanation.

The work illuminates the psychological foundations of style perception and enables further investigation of styled media using psychophysical and computational approaches.


Based on the context: 'Extinction learning suppresses fear responses and is central to understanding anxiety disorders, but it is unclear whether rodent findings on amygdala/hippocampal theta oscillations and context-dependent engrams apply to humans or how they relate to episodic memory mechanisms.', the key idea: 'The study investigates human extinction learning by combining intracranial EEG with representational similarity analysis, proposing that extinction relies on stable, context-specific memory traces coordinated across the extinction network and that amygdala theta oscillations signal safety rather than threat.', the method: 'Intracranial EEG recordings from epilepsy patients during fear and extinction learning were analyzed alongside representational similarity analysis to characterize cue- and context-specific memory traces and their coordination, including assessments of theta oscillations and predictive relationships tested in a subsequent period.', and the outcome: 'Amygdala theta oscillations during extinction signaled safety; extinction memory traces were stable, context-specific, and coordinated across the network; context specificity during extinction predicted reoccurrence of fear memory traces at test, and reoccurrence of extinction memory traces predicted safety responses; mutual competition of fear and extinction traces explains fear renewal and extinction retrieval.', suggest the projected impact for this research. Output only the impact without explanation.

The findings reveal neurophysiological mechanisms of human context-dependent extinction learning and suggest a mechanistic framework for clinically relevant phenomena such as fear renewal and extinction retrieval, with potential implications for understanding and treating anxiety disorders.


Based on the context: 'Prevailing accounts treat social learning strategies as fixed heuristics independent of experience, which cannot explain the observed flexibility and individual variability in whom people choose to learn from.', the key idea: 'A domain-general, feature-based reward learning framework is proposed that formalizes how individuals learn to associate social features (such as others’ behavior or success) with reward, providing a unifying mechanistic account of social learning strategies.', the method: 'Six experiments (n=1,941) measure adjustments in social learning in response to experienced rewards, complemented by agent-based simulations that examine how the learning process generates key social learning strategies across different environments.', and the outcome: 'People flexibly adjust their social learning based on experienced rewards, and simulations demonstrate that this learning mechanism produces canonical social learning strategies across diverse environments.', suggest the projected impact for this research. Output only the impact without explanation.

The framework suggests that individuals learn how to learn from others, enabling adaptive knowledge to spread dynamically and informing theories of cultural evolution.


Based on the context: 'Time spent on the job is a fundamental aspect of working conditions that influences many facets of individuals’ lives, motivating examination of how a 4-day workweek affects workers’ well-being.', the key idea: 'Evaluate an organization-wide, income-preserving 4-day workweek intervention, preceded by work reorganization to improve efficiency and collaboration, to assess impacts on worker well-being.', the method: 'Pre- and post-trial analysis of a 6-month intervention across 141 organizations in Australia, Canada, Ireland, New Zealand, the UK, and the USA with 2,896 employees, including 12 control companies; outcomes measured included burnout, job satisfaction, mental health, and physical health; correlations between company- and individual-level hours reductions and well-being gains were examined, along with mediation by work ability, sleep problems, and fatigue.', and the outcome: 'The intervention improved burnout, job satisfaction, mental health, and physical health, effects not seen in control companies; both company- and individual-level hours reductions correlated with well-being gains, with larger individual-level reductions associated with greater improvements; improved work ability, reduced sleep problems, and decreased fatigue mediated the gains.', suggest the projected impact for this research. Output only the impact without explanation.

Findings indicate income-preserving 4-day workweeks are an effective organizational intervention for enhancing workers’ well-being, suggesting a viable practice for employers and policymakers.


Based on the context: 'Predicting human decisions under risk and uncertainty is a longstanding challenge, with existing models struggling even in stylized lottery-choice tasks.', the key idea: 'A hybrid model, BEAST gradient boosting (BEAST-GB), integrates the behavioural theory BEAST with machine learning to improve prediction of risky choices.', the method: 'The model was evaluated via the CPC18 prediction competition and tested on two large datasets, with comparisons against neural networks and dozens of behavioural models, including assessments of generalization to unseen experimental contexts.', and the outcome: 'BEAST-GB won CPC18, predicted more accurately than neural networks and many behavioural models, generalized robustly across unseen contexts, surpassed direct empirical generalization, and helped refine the behavioural theory itself.', suggest the projected impact for this research. Output only the impact without explanation.

Anchoring machine learning in behavioural theory can enable more accurate and interpretable predictions in data-rich settings and improve understanding of human behaviour.


Based on the context: 'Occupational specialization is tied to gender, racial, and class identities, segmenting the labor market into perceived White/Black and male/female roles and skill sets.', the key idea: 'The study differentiates how segregation operates by showing that gender divisions align with required occupational skills, whereas racial divisions align with socio-economic status and historical inequalities within skill sets.', the method: 'A large-scale analysis of administrative data from 100 million formal Brazilian workers (2003–2019) across 426 occupations, identifying distinct skill demands and socio-economic statuses linked to race/skin colour and gender.', and the outcome: 'Women and men are segmented by gender-associated skill sets (e.g., engineering versus caregiving), while within these skill sets Black individuals are disproportionately concentrated in lower socio-economic status positions; these occupational specialization patterns remained stable despite recent socio-economic changes.', suggest the projected impact for this research. Output only the impact without explanation.

The findings highlight the need to address the strong association between race and lower-status occupations to foster a more inclusive society.


Based on the context: 'Persistent neural activity is known to support working memory when memorized items have equal importance, but how unattended items are encoded—often presumed to be ‘activity-silent’—is poorly understood.', the key idea: 'Unattended working memory items, like attended ones, are proposed to be encoded via persistent activity in human medial temporal lobe neurons, challenging the ‘activity-silent’ account.', the method: 'Neuronal recordings from image-selective medial temporal lobe cells in human subjects (n=12) during tasks requiring shifts of attention between concurrently stored items, with decoding analyses at single-trial and population levels.', and the outcome: 'Both attended and unattended items were encoded through persistent activity; a dynamic transformation in neuronal subspace emerged after cue presentation; unattended item information was decodable at the single-trial level from preselected image-selective cells but not from the entire medial temporal lobe population.', suggest the projected impact for this research. Output only the impact without explanation.

Findings support models of persistent activity in working memory and challenge the notion that unattended items rely on ‘activity-silent’ mechanisms.


Based on the context: 'Healthy diets have been associated with reduced dementia risk, motivating data-driven optimization of dietary interventions beyond a priori patterns.', the key idea: 'A machine learning-assisted approach constructs an optimized dietary pattern (MODERN diet) and a MODERN score to better capture foods linked to lower dementia risk.', the method: 'Using 185,012 UK Biobank participants over 10 years, the study conducted a food-wide association analysis to identify 25 food groups, ranked their importance with machine learning to prioritize eight, built and externally validated a 0–7 MODERN score, examined associations across 63 health outcomes, and explored pathways via multimodal neuroimaging, metabolomics, inflammation and proteomics.', and the outcome: 'The MODERN score showed stronger associations with lower dementia-related risk (HR highest vs lowest tertiles: 0.64, 95% CI: 0.43–0.93) than the MIND diet (0.75, 0.61–0.92), had notable associations with mental/behavioral disorders, and biomarker analyses revealed potential pathways.', suggest the projected impact for this research. Output only the impact without explanation.

The MODERN diet is proposed as a promising strategy for dementia prevention and may inform future mechanistic research and intervention trials.


Based on the context: 'Although large language models exhibit social–emotional abilities that could support human–AI interactions, it remains unclear whether empathy is perceived differently when attributed to AI versus humans.', the key idea: 'The study tests whether perceived empathy depends on the attributed source by labeling identical AI-generated empathic responses as coming from humans or AI, and examines preferences for human versus AI emotional engagement.', the method: 'Across nine studies (n=6,282), participants received AI-generated empathic responses to their emotional situations that were labeled as human- or AI-provided; the experiments varied response lengths, delays, iterations, and large language models, and measured perceived empathy, support, emotional reactions, and interaction choices.', and the outcome: 'Human-attributed responses were rated as more empathic and supportive and elicited more positive and fewer negative emotions than AI-attributed ones; participants’ belief that AI aided human-attributed responses reduced perceived empathy and support; effects replicated across manipulations and were primarily driven by responses emphasizing emotional sharing and care; participants consistently preferred human interaction for emotional engagement.', suggest the projected impact for this research. Output only the impact without explanation.

The findings advance understanding of empathy and human–AI empathic interactions, clarifying the unique value of human-attributed empathy.


Based on the context: 'There is widespread concern that consuming news on social media leaves people uninformed or misinformed.', the key idea: 'The study tests whether following news organizations on Instagram and WhatsApp improves knowledge, belief accuracy, and trust compared to following non-news accounts.', the method: 'A preregistered two-wave online field experiment in France and Germany (N=3,395) asked participants to follow two accounts for 2 weeks with notifications on; treatment participants followed news organization accounts and controls followed accounts on cooking, cinema or art, with outcomes measured across information and attitude domains.', and the outcome: 'Following news accounts increased current affairs knowledge, the ability to discern true from false news stories, awareness of true news stories, and trust in the news, with no significant effects on feelings of being informed, political efficacy, affective polarization, or interest in news or politics.', suggest the projected impact for this research. Output only the impact without explanation.

The findings indicate that certain forms of social media use are beneficial and can be leveraged to foster a well-informed society.


Based on the context: 'Strategic decision-making is a crucial part of human interaction, and previous datasets and theories have not captured the full complexity of initial play in two-player matrix games.', the key idea: 'Apply machine learning to predict human strategic choices and develop an interpretable behavioural model, using a deep neural network to capture systematic variation beyond leading theories.', the method: 'Analyze over 90,000 human decisions across more than 2,400 procedurally generated two-player matrix games; train a deep neural network on this dataset and modify it to build an interpretable model.', and the outcome: 'The deep neural network predicts human choices more accurately than leading theories and reveals systematic variation unexplained by existing models; the interpretable model shows that optimal responding and reasoning about others are highly context dependent and influenced by game complexity.', suggest the projected impact for this research. Output only the impact without explanation.

Demonstrates the potential of machine learning to generate new theoretical insights into complex human behaviours.


Based on the context: 'Co-offending—crimes committed by two or more individuals—is shaped by social processes like peer influence and group cohesion, and studying it elucidates how relationships affect criminal decision-making.', the key idea: 'A comprehensive synthesis quantifies co-offending by providing pooled estimates of prevalence and group size and examines variations by crime type, age, and gender using a Bayesian meta-analytic framework.', the method: 'A preregistered systematic review and Bayesian meta-analysis aggregated data from 110 studies across 17 countries, analyzing prevalence of co-offences, prevalence of co-offenders, and average group size with large samples of offences and offenders, and comparing subgroups by offence type, age, and sex.', and the outcome: 'Pooled prevalence of co-offences was 0.29 (95% CrI 0.22–0.35), prevalence of co-offenders was 0.50 (95% CrI 0.43–0.56), and average group size was 2.73 (95% CrI 2.63–2.84); property crimes had higher prevalence of co-offending than violent crimes, violent offences involved larger groups, youth co-offended more and in larger groups than adults, and males formed larger groups with no notable sex differences in co-offender prevalence.', suggest the projected impact for this research. Output only the impact without explanation.

Findings highlight challenges due to heterogeneous reporting and underscore the need for standardized measures, offering benchmarks to guide future research and policy on the social dynamics of crime.


Based on the context: 'People not only form social networks, they construct mental maps of them, motivating examination of the accuracy and biases in these cognitive representations.', the key idea: 'A new sampling strategy is introduced to evaluate social network cognition at scale by comparing observers’ beliefs about ties to systematically mapped village networks, including genetic relatedness in a subset of villages.', the method: 'Data were collected from 10,072 adults across 82 Honduran villages to elicit judgments of social ties and map the underlying village networks; in 17 villages, genetic relatedness of 1,333 residents was discerned, and an experimental information introduction to peers assessed information access among respondents.', and the outcome: 'Observers overestimated social interactions among kin and were 33.38 percentage points more accurate for non-kin ties (95% CI: 31.27–35.49); accuracy was higher among popular, middle-aged, and educated observers, lower across different religions or wealth, and villages cultivating coffee showed greater bias toward seeing networks as connected. More accurate respondents had better access to experimentally introduced information, and overall people inflated the number of connections in their networks.', suggest the projected impact for this research. Output only the impact without explanation.

Findings indicate that biases and accuracy in network cognition have implications for how people affect and are affected by the social world.


Based on the context: 'Humans solve complex multistage decision problems using hierarchical and counterfactual strategies, but the computational constraints underlying these strategies are not well understood.', the key idea: 'The study proposes that hierarchical, counterfactual, and postdictive strategies are computationally rational adaptations to specific cognitive constraints and that these strategies lie along a continuum.', the method: 'A task was designed to reliably engage hierarchical and counterfactual strategies, followed by hypothesis-driven human experiments to identify constraints, and training recurrent neural networks under systematically varied limitations to test for human-like behavior.', and the outcome: 'Three constraints were identified—a parallel-processing bottleneck that promotes hierarchical analysis, a compensatory but capacity-limited counterfactual process, and working-memory noise that reduces counterfactual fidelity—and only recurrent neural networks subjected to all three reproduced human-like behavior; further analysis showed these strategies form a continuum of rational adaptations.', suggest the projected impact for this research. Output only the impact without explanation.

The findings suggest a unifying framework in which human decision strategies emerge from shared computational limitations, enhancing understanding of cognitive flexibility and efficiency.


Based on the context: 'Individual sensitivity to environmental exposures may be genetically influenced, yet variants underlying genotype-by-environment interplay are hard to detect and population-based methods can suffer from systemic biases.', the key idea: 'Use genome-wide association studies of monozygotic twin differences via family-based variance analyses as an alternative, more robust approach to study the genetic architecture of environmental sensitivity in psychiatric and neurodevelopmental phenotypes.', the method: 'Combined data from 21,792 monozygotic twins (10,896 pairs) across 11 studies and conducted GWAS meta-analyses of twin phenotypic differences in children, adolescents, and adults for seven traits (ADHD symptoms, autistic traits, anxiety/depression symptoms, psychotic-like experiences, neuroticism, wellbeing), using family-based variance analyses.', and the outcome: 'Estimated SNP-based proportions of phenotypic variance (h2 = 0–18%) with imprecision, and identified 13 genome-wide significant associations including genes related to stress reactivity for depression, growth factors for autistic traits, and catecholamine uptake for psychotic-like experiences; the study is the largest genetic analysis of monozygotic twins to date, with limited statistical power in some analyses.', suggest the projected impact for this research. Output only the impact without explanation.

Demonstrates an alternative method for investigating environmental sensitivity genetics and calls for better-powered future studies.


Based on the context: 'Human amygdala and hippocampus neurons are classically thought to encode person identity invariant to visual features, yet how visual information from higher visual cortical areas is transformed into a semantic person representation remains largely unknown.', the key idea: 'The study demonstrates a region-based feature code for faces, where single neurons encode faces based on shared visual features rather than associations of known concepts, contrary to prevailing views.', the method: 'Across four experiments, single-neuron recordings were obtained from 3,581 neurons in 19 neurosurgical patients over 111 sessions, analyzing feature-based responses and using receptive fields to predict responses to new face stimuli.', and the outcome: 'Feature neurons encoded groups of faces irrespective of identity, broad semantic categories, or familiarity, and the neurons’ receptive fields predicted their responses to novel face stimuli, supporting feature-based encoding in the human amygdala and hippocampus.', suggest the projected impact for this research. Output only the impact without explanation.

Discovering neurons that bridge perception-driven facial feature representations with mnemonic semantic representations may form the basis for declarative memory.


Based on the context: 'Primate vision exhibits topographic organization, but standard convolutional neural networks learn identical features across space and lack topography, limiting their ability to model cortical maps and related behaviours.', the key idea: 'The study introduces all-topographic neural networks (All-TNNs) as end-to-end models that naturally develop primate-like topographic maps and can capture spatially structured processing while operating efficiently.', the method: 'Researchers designed and trained All-TNNs, analyzed their learned orientation and category selectivity maps and energy usage, and validated them against human behaviour using a newly collected dataset of spatial biases in object recognition, comparing performance to control models.', and the outcome: 'All-TNNs developed smooth orientation and category selectivity maps, showed enhanced processing of task-relevant regions, operated on a low energy budget, and significantly outperformed control models in predicting human spatial biases in object recognition.', suggest the projected impact for this research. Output only the impact without explanation.

All-TNNs are proposed as a promising framework for modelling primate visual topography and elucidating its role in downstream human visual behaviour.


Based on the context: 'Prior evidence on the development of scene viewing is limited and has suggested that viewing behavior may be adult-like by around eight years old.', the key idea: 'The study proposes that gaze behavior develops protractedly, with adult-like spatial and semantic viewing biases emerging gradually over up to two decades, challenging earlier assumptions of early maturation.', the method: 'Eye movements from 6,720 participants aged 5 to 72 were recorded while freely viewing 40 natural scenes, including a large-scale museum setting, to analyze semantic salience, oculomotor biases, exploration tendencies, and fixation patterns across age.', and the outcome: 'Semantic salience for social features changes until adolescence; text salience increases across the first two decades; oculomotor center and horizontal biases develop until adolescence; exploration increases while fixation patterns become less idiosyncratic and more canonical through adolescence.', suggest the projected impact for this research. Output only the impact without explanation.

The findings suggest that developmental trajectories are crucial for understanding the general mechanisms of active vision.


Based on the context: 'Beliefs underpin human cognition and decision-making, yet research on how beliefs interrelate has been limited to issue-specific studies and has relied heavily on surveys, lacking a model that encapsulates beliefs and their interrelationships.', the key idea: 'Leverage online user debate data to map thousands of beliefs into a semantic embedding space constructed with a fine-tuned large language model, capturing nuanced relationships, interconnectedness, and polarization among diverse beliefs.', the method: 'Fine-tune a large language model on debate data to build neural belief embeddings, map individual positions within this space, and use distances to analyze relationships, predict new beliefs, and estimate cognitive dissonance.', and the outcome: 'The constructed belief space captures interconnectedness and polarization across social issues; positions within the space predict individuals’ new beliefs and allow estimation of cognitive dissonance from distances between existing and new beliefs.', suggest the projected impact for this research. Output only the impact without explanation.

Shows that LLM-based belief embeddings combined with online records can yield insights into fundamental principles of belief formation, suggesting a scalable alternative to survey-based approaches for studying belief interplay.


Based on the context: 'The necessity of multisensory grounding for complex concept formation is debated, and recent large language models challenge whether language alone can yield human-like conceptual representations.', the key idea: 'Assess whether ungrounded LLMs recover human-like features by comparing their conceptual representations to human norms across non-sensorimotor, sensory, and motor domains, and test whether visual learning improves alignment.', the method: 'Compared multidimensional representations of approximately 4,442 lexical concepts from the Glasgow Norms (N=829) and the Lancaster Norms (N=3,500) with state-of-the-art LLMs with and without visual learning, evaluating similarity across domain types.', and the outcome: 'Similarity between model and human representations decreases from non-sensorimotor to sensory domains and is minimal in motor domains; models with visual learning show enhanced similarity in visual-related dimensions.', suggest the projected impact for this research. Output only the impact without explanation.

Findings highlight limitations of language-only training and suggest that integrating diverse modalities can better align LLM conceptual representations with human cognition.


Based on the context: 'Social media offers direct channels for science communication, but only a subset of academics engage, potentially shaping public perceptions through their topics and tone.', the key idea: 'The study systematically characterizes academics’ politically salient expression on Twitter by linking nearly 100,000 scholars’ tweets to their academic records and comparing their communication with broader Twitter populations.', the method: 'An observational analysis of an international dataset of nearly 100,000 academics links Twitter content to academic records and examines politically salient topics (climate action, cultural and economic concepts), including comparisons with the US Twitter population.', and the outcome: 'The study finds large, systematic variation in political expression; US academics often diverge from the US Twitter population in topic focus and style; academics are not necessarily more extreme in beliefs; strong progressive stances on climate and social issues are driven by a small, vocal subset, highlighting potential gaps between academic voices and public discourse.', suggest the projected impact for this research. Output only the impact without explanation.

Future work should examine the implications for public trust and the reasons why academics express themselves politically on social media.


Based on the context: 'Political animosity is rising and threatens democracy, and while intergroup contact and mutually beneficial cooperation are known to reduce animosity, it is unclear whether this can be achieved in anonymous online contexts.', the key idea: 'A cooperative online quiz game (Tango) pairs Republicans and Democrats to engage in real-time, mutually beneficial cooperation to reduce outparty animosity.', the method: 'Five randomized controlled experiments (N=4,493; four preregistered) had participants play about an hour with an outparty partner in an online quiz game while communicating in real time, measuring negative partisanship, warmth, economic allocations, meta-perceptions, and democracy-related attitudes with follow-ups up to four months.', and the outcome: 'Gameplay with an outparty partner reduced negative partisanship; increased warmth, more equitable economic allocations, and more favorable outparty meta-perceptions persisted up to four months; democracy-related attitudes improved with effects persisting for one week; the game received high enjoyability ratings.', suggest the projected impact for this research. Output only the impact without explanation.

High enjoyability may increase motivation to engage with this intervention.


Based on the context: 'Human habit formation is commonly studied via learning arbitrary stimulus–response associations, with habitualness assessed by withholding responses or generating different responses; prior studies using these methods have yielded conflicting findings.', the key idea: 'The discrepancy in findings is proposed to stem from the fact that the two methods target distinct forms of habit linked to different components of action control: response initiation versus response preparation.', the method: 'A series of experiments with a total sample size of 215 participants, complemented by computational modeling, compare tasks that probe response initiation and response preparation to assess their dissociability.', and the outcome: 'The studies demonstrate that the two approaches indeed measure dissociable forms of habit, showing that behavior can become habitual in multiple, qualitatively different ways.', suggest the projected impact for this research. Output only the impact without explanation.

The results imply important avenues for improving strategies to promote or eliminate habits by targeting specific components of action control.


Based on the context: 'Inhibitory control is critical for daily functioning and psychiatric disorders, yet the widely used congruency effect has low reliability, limiting its utility in clinical and basic research.', the key idea: 'The study investigates whether precise individual estimates of the congruency effect can be obtained, proposing that extensive within-person sampling is necessary to achieve reliable measures.', the method: 'More than 5,000 trials were collected from nine participants across four inhibitory control tasks, and a combination of datasets and simulations was used to assess reliability; the dataset is made publicly available.', and the outcome: 'Precise individual estimates of the congruency effect are achievable but require substantially more trials than typical, with over 1,000 trials per participant needed to reduce within-participant variability and improve reliability; extensive sampling reveals true individual differences and improves observations from alternative modeling approaches.', suggest the projected impact for this research. Output only the impact without explanation.

The publicly shared dataset is intended to help researchers understand sources of variation in inhibitory control and to advance research in this field.


Based on the context: 'Autism spectrum disorder is clinically heterogeneous, with ongoing debates about phenotypic differences between boys and girls; identifying such differences at first symptom onset is considered critical for early detection, aetiological insights, and intervention improvement.', the key idea: 'A large-scale, early-age, multi-method assessment examines sex differences in toddlers with ASD, developmental delay, and typical development across standardized and experimental measures to determine whether sex differences are present at first symptom onset.', the method: 'Using the Get SET Early programme, the study analyzed 2,618 toddlers (mean age ~27 months) via cross-sectional, longitudinal, and clustering analyses employing statistical and machine learning approaches across groups, with measures including the Autism Diagnostic Observation Schedule, Mullen Scales of Early Learning, and the GeoPref eye-tracking test.', and the outcome: 'There were no significant sex differences in toddlers with ASD across 17 of 18 measures, including symptom severity, receptive and expressive language, and social attention; in contrast, typically developing girls outperformed boys on several measures, and subtyping into low, medium, and high clusters similarly showed virtually no sex differences in ASD.', suggest the projected impact for this research. Output only the impact without explanation.

Findings indicate early ASD phenotypes may be largely sex-invariant, which could inform early detection efforts, guide aetiological research, and improve intervention strategies.


Based on the context: 'Understanding gene–environment interaction in complex traits is crucial, but existing statistical methods for GxE inference struggle with scalability and interpretability.', the key idea: 'PIGEON is a unified variance component framework for quantifying polygenic GxE that enables summary statistics–based estimation and clarifies objectives for GxE studies.', the method: 'The study develops a variance component analytical approach that uses only summary statistics and validates it through theoretical analysis and empirical applications, including a quasi-experimental gene-by-education study, gene-by-sex interaction analyses for 530 traits in UK Biobank, and a clinical trial on smoking cessation.', and the outcome: 'PIGEON was demonstrated to be effective in estimating polygenic GxE, successfully analyzing gene-by-education effects on health outcomes, quantifying gene-by-sex interactions across 530 UK Biobank traits, and identifying genetic interactors explaining treatment effect heterogeneity in a smoking cessation trial.', suggest the projected impact for this research. Output only the impact without explanation.

The framework provides a path toward scalable, interpretable, polygenic GxE inference using summary statistics, guiding future genome-wide interaction studies.