The research, conducted by Xiaoqing Jiang, is built around a concept that has gained traction in governance scholarship: co-governance participation intention, meaning a resident’s stated willingness to take part in collaborative decision-making about tourism in their community. This is not merely a matter of attending the occasional town meeting. In destinations under sustained tourism pressure, residents are increasingly invited — or expected — to share responsibility for managing crowding, protecting local heritage, mediating conflicts with visitors, and shaping the rules that determine who benefits from tourism and who bears its costs. Understanding what motivates that willingness is therefore central to whether collaborative governance actually works or remains a slogan on a planning document.

To probe the question, the study drew on organizational justice theory, which distinguishes three dimensions of fairness. Distributive justice concerns the perceived fairness of outcomes: whether the benefits and burdens of tourism — income, opportunity, congestion, noise, rising costs — are shared in ways residents consider equitable. Procedural justice concerns the fairness of the processes by which decisions are made: whether rule-making is transparent, consistent, and open to genuine resident voice. Interactional justice concerns the quality of interpersonal treatment: whether residents feel they are treated with dignity and respect by authorities, and, in this study’s framing, in the everyday encounters that tourism generates. The survey instrument measured residents’ perceptions across all three dimensions, alongside their emotional solidarity with tourists — feelings of warmth, welcome, and identification with visitors — and their intention to participate in co-governance.

Analyzing the data with structural equation modeling, the study found that all three dimensions of perceived justice were positively associated with both emotional solidarity and co-governance participation intention. In other words, residents who perceived tourism governance as fair — in its outcomes, its procedures, and its interpersonal treatment — reported stronger feelings of emotional connection with tourists and a greater willingness to engage in collaborative management. Notably, the associations for procedural and interactional justice were particularly strong. The fairness of how decisions are made, and the respect conveyed in day-to-day interactions, mattered at least as much as — and in these data, more saliently than — the distribution of material benefits alone.

This pattern challenges a persistent assumption in destination management: that keeping residents satisfied is primarily a matter of distributing tourism revenue, subsidies, jobs, or compensation. Those material flows certainly matter, and distributive justice did show a positive association with both emotional solidarity and participation intention. But the stronger signals from procedural and interactional justice suggest that residents evaluate tourism governance through a broader relational lens. A community meeting that genuinely solicits resident input, a complaint channel that actually responds, a tourism official who treats a local shopkeeper’s concerns as legitimate — these everyday experiences of fairness appear to feed directly into residents’ sense that co-governing tourism is worthwhile.

The study then tested a mediation pathway, asking whether emotional solidarity with tourists serves as a bridge between governance fairness and participation intention. The mediation analysis indicated a significant indirect association: perceived justice was linked to participation intention partly through residents’ emotional solidarity with visitors. This finding adds an intriguing psychological mechanism to the picture. Fair governance, it appears, does not only persuade residents that the system is legitimate; it also seems to soften the social boundary between hosts and guests. Residents who feel fairly treated become, in a measurable sense, warmer toward the tourists whose presence their governance must accommodate — and that warmth, in turn, is associated with a stronger intention to participate in managing tourism collectively.

The logic behind this pathway is worth unpacking, because it links two research literatures that have often run in parallel. Work on emotional solidarity in tourism, rooted in Durkheimian sociology and later formalized in host–guest relationship models, has shown that residents’ affective bonds with tourists influence their support for tourism development. Work on organizational justice has shown that fair treatment builds trust in institutions and willingness to cooperate with them. The Wuxi study connects the two: fairness in governance is not only institutional but relational, and its effects ripple outward from how residents regard their government to how they regard their guests. A resident who perceives that the tourism system treats her fairly may extend a presumption of goodwill to the visitors that system brings to her doorstep — and a resident who feels goodwill toward visitors has a richer emotional reason to help govern the destination than mere economic self-interest alone.

The study also examined whether perceived tourism pressure — the degree to which residents experience crowding, disruption, and strain from visitor numbers — changed these relationships. Here the results were more selective than one might expect. Perceived tourism pressure significantly moderated only one pathway: the association between interactional justice and emotional solidarity. It did not significantly moderate the associations for distributive or procedural justice. In practical terms, this suggests that respectful interpersonal treatment matters most, or works differently, when tourism pressure is high. When the streets are crowded and tempers are short, the quality of everyday encounters between hosts and guests — and between residents and those who govern tourism — becomes a more decisive factor in whether residents maintain emotional solidarity with visitors. Meanwhile, the links between distributive and procedural fairness and emotional solidarity appear comparatively robust across levels of tourism pressure, suggesting that these forms of fairness operate as a steadier foundation regardless of how heavy the visitor burden becomes.

For destination managers and municipal planners, the findings point toward a specific agenda. Transparent procedures, meaningful resident voice, and respectful everyday interactions are not soft extras bolted onto a tourism strategy; in this study they carry the strongest associations with residents’ willingness to co-govern. That has concrete implications for how participatory mechanisms are designed. Consultation exercises that exist to legitimize decisions already made are unlikely to build the kind of fairness perception that motivates engagement. What appears to matter is procedural authenticity — genuine opportunities for residents to influence outcomes — combined with interactional care in every point of contact between the tourism apparatus and the community it affects. The moderation results add a further nuance: as tourism pressure intensifies, investing in the quality of everyday interactions may become even more critical for preserving the emotional bonds that sustain collaborative governance.

The study’s scope and method frame how far its conclusions travel. It relies on cross-sectional survey data from 308 residents in one Chinese city, analyzed through structural equation modeling, mediation analysis, and hierarchical regression; the associations reported are just that — associations, not experimentally established causes. Emotional solidarity and participation intention are measured as perceptions and stated intentions rather than observed behavior, and residents of Wuxi’s major attraction areas may differ from those of other destinations in ways that shape the results. Still, the core contribution stands: collaborative tourism governance is not sustained by institutional design alone, nor by economic compensation alone, but by a relational fabric that runs from the fairness of decision procedures, through the emotional bond between hosts and guests, to residents’ readiness to share the work of governing. In destinations around the world now grappling with overtourism, that insight reframes the problem. The question is not only how to divide tourism’s benefits, but how to govern — and simply treat people — in ways that make residents want to be part of the answer.

Subject of Research: Associations between perceived governance justice, emotional solidarity with tourists, and residents' co-governance participation intention in tourism-affected communities

Article Title: Justice under tourism pressure: Governance fairness, emotional solidarity, and residents’ co-governance participation intention in tourism-affected communities

Article References: Jiang, X. (2026). Justice under tourism pressure: Governance fairness, emotional solidarity, and residents’ co-governance participation intention in tourism-affected communities. PLOS One, 21(10), e0360394. https://doi.org/10.1371/journal.pone.0360394

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360394

Keywords: tourism governance, co-governance, organizational justice, distributive justice, procedural justice, interactional justice, emotional solidarity, overtourism, resident participation, Wuxi China, structural equation modeling, destination management

The research team conducted a rapid review of global case studies, a method designed to synthesize a broad and scattered evidence base within a structured analytical frame. Rather than cataloguing individual examples of unfairness, the authors interrogated the accumulated evidence to identify where and how climate action is engaging with the core pillars of justice that political philosophers and environmental justice scholars have developed over decades. Their conclusion is both encouraging and cautionary. The three classical dimensions of justice—distributive, procedural, and recognitional—are indeed being engaged with in urban climate initiatives worldwide, but the depth and simultaneity of that engagement determines whether an intervention becomes genuinely transformative or merely cosmetic.

Distributive justice, the first pillar, concerns who receives the benefits and burdens of climate policy. In practical terms, it asks whether a new flood barrier protects wealthy waterfront districts while informal settlements remain exposed, or whether urban tree-planting programs cool already leafy neighborhoods while heat-vulnerable districts stay bare. The review finds that cities increasingly deploy joint mitigation and adaptation interventions—projects that reduce emissions while building resilience—and that the distributional question is now explicitly on the agenda in many of them. Yet distribution alone is a blunt instrument. A solar subsidy program can be perfectly equal in formal terms and still be inaccessible to renters, low-income households, or residents without legal tenure, which is why the authors insist that distributional analysis must be paired with the other pillars.

Procedural justice addresses the second dimension: who participates in deciding. It examines whether affected communities have genuine voice in the design, implementation, and evaluation of climate interventions, or whether participation is reduced to token consultation after the key decisions have been made. The synthesized case studies show that exclusionary governance remains one of the most persistent barriers to equitable urban climate action. When planning processes are technically opaque, conducted in dominant languages only, or scheduled in ways that exclude working residents, the resulting policies tend to reproduce the very vulnerabilities they claim to address. The review identifies procedural reforms—co-production of plans with communities, transparent decision criteria, and accountability mechanisms—as a recurring feature of the more successful pathways.

Recognitional justice, the third classical pillar, goes deeper still. It asks whether the identities, histories, and knowledge systems of marginalized groups are respected within climate governance. Recognition failures can be subtle: Indigenous worldviews dismissed as irrelevant to technical flood modeling, gendered patterns of climate vulnerability ignored in mobility planning, or the specific exposures of migrants and ethnic minorities rendered invisible in aggregate city statistics. The authors find that recognition is increasingly invoked in climate action, but that it is often the thinnest of the three pillars in practice, acknowledged in policy language without changing who holds power or whose knowledge counts.

This is where the paper’s conceptual contribution becomes significant. The team extends the standard triad by integrating two additional dimensions: epistemic justice and restorative justice. Epistemic justice concerns the credibility afforded to different kinds of knowledge. In urban climate contexts, this means treating residents’ lived experience of flooding or heat as legitimate evidence alongside satellite data and hydrological models, and creating institutional channels through which local and Indigenous knowledge can genuinely inform technical decisions. Restorative justice, meanwhile, addresses deeply rooted systemic exclusions by confronting historical wrongs—colonial dispossession, discriminatory housing policy, and the extraction that built urban wealth in some places at the expense of others. A city cannot simply plan forward from an unjust baseline, the framework suggests; it must also account for how that baseline was produced.

The central analytical claim of the review is that climate initiatives are more likely to become transformative when they address multiple dimensions of justice simultaneously. This is a testable proposition with real design implications. A cooling center program that distributes resources fairly (distributive), is sited through community deliberation (procedural), respects the needs of elderly residents and informal workers (recognitional), incorporates their knowledge of neighborhood microclimates (epistemic), and acknowledges past disinvestment in their districts (restorative) is structurally different from a program that scores well on only one axis. The authors argue that single-pillar interventions tend to stall or backslide, because unresolved injustices in other dimensions eventually undermine them—participation without recognition becomes tokenism, and recognition without redistribution becomes symbolism.

From the synthesized evidence, the researchers distill key principles for enabling just and equitable action. While the review is careful not to prescribe a single template—urban contexts vary enormously between, say, a rapidly growing South Asian megacity and a shrinking post-industrial city in Europe—the principles converge on a common logic. Justice must be embedded from the earliest stages of intervention design rather than retrofitted after opposition emerges. Power must be genuinely shared with the communities who bear climate risks. Knowledge hierarchies that privilege formal expertise must be opened to plural ways of knowing. And institutions must be built to sustain these practices over time, because justice is not a one-time consultation but an ongoing condition of governance.

The practical payoff of the framework is a shift in what the field asks of research. As the authors put it in their abstract, the work is intended to move researchers and practitioners beyond identifying climate injustices toward an actionable roadmap for co-producing equitable climate solutions. Co-production is the operative term: the pathways the review maps are not top-down blueprints delivered to passive beneficiaries, but collaborative processes in which residents, municipal agencies, researchers, and civil society organizations jointly define problems and solutions. This framing reflects a broader movement in sustainability science over the past decade, but the review gives it sharper normative teeth by insisting that the quality of co-production be judged against all five justice dimensions.

The timing of this synthesis matters. Urban populations continue to grow fastest precisely in regions with the highest climate exposure and the weakest adaptive capacity, and national governments remain slow to deliver the finance and institutional support cities need. In that gap, municipal governments, community organizations, and hybrid actors are improvising climate action on their own—and the review’s evidence suggests that those improvisations succeed most often when justice is treated as constitutive of effectiveness rather than as a constraint on it. The authors declare no competing financial interests, and the paper is published open access, making the framework available to the practitioners it is meant to serve. What the study ultimately offers is a vocabulary and a checklist for a question that every city will face this century: not simply whether climate action happens, but who it is for, who decides, and whose past it repairs.

Subject of Research: Urban climate justice frameworks for equitable mitigation and adaptation in cities

Article Title: Overcoming urban climate injustice: synthesising global pathways and principles

Article References: Prakash, A., Bulkeley, H. A., Singh, C., McGregor, D., & George, R. (2026). Overcoming urban climate injustice: synthesising global pathways and principles. npj Urban Sustainability. https://doi.org/10.1038/s42949-026-00477-z

Image Credits: AI Generated

DOI: 10.1038/s42949-026-00477-z

Keywords: urban climate justice, climate adaptation, climate mitigation, distributive justice, procedural justice, recognitional justice, epistemic justice, restorative justice, co-production, urban sustainability, climate governance, rapid review

Payment for Ecosystem Services, commonly abbreviated as PES, is a policy instrument that translates the ecological work performed by natural systems into economic value. In a water context, this might mean compensating landowners for maintaining forested catchments that filter rainfall naturally, rewarding farmers for reducing nutrient runoff into rivers, or funding the restoration of urban wetlands that buffer neighbourhoods against flooding. The underlying logic is that when the beneficiaries of a healthy watershed—utilities, municipalities, residents—contribute financially to its upkeep, the incentives for conservation become embedded in everyday economic decisions rather than resting solely on regulation or goodwill. What distinguishes PES4URBANWATER from earlier work, however, is its explicit focus on systemic services and on the fairness of how costs and benefits are distributed.

The project will analyze how payments for systemic services can improve water quality, protect water resources and support climate change adaptation through an equitable approach across different organizational contexts. That emphasis on equity is not incidental. Previous studies have often assessed the economic or environmental feasibility of PES schemes in isolation, asking whether they deliver measurable improvements in water quality or whether they generate a positive return on investment. PES4URBANWATER instead places distributive justice at the heart of its analysis, examining how the burdens and benefits of urban water management models are actually shared among the communities, institutions and industries involved.

Dr Cecilia Higa Gonzales Morilla, an MSCA Postdoctoral Fellow working on the project, framed the rationale in stark terms. A water management model, she explained, is only truly viable if its burdens and benefits are distributed fairly and transparently. By comparing contexts such as Barcelona and Melbourne, the research team aims to demonstrate that environmental protection, financial viability and social justice are three deeply interconnected dimensions that must be managed together rather than traded off against one another. That framing challenges a long-standing tendency in environmental economics to treat equity as a secondary consideration—something to be addressed after efficiency has been secured—rather than as a precondition for durable policy.

The choice of case studies is central to the project’s analytical power. Barcelona and Melbourne were selected because they operate two distinct and pioneering water governance models. Barcelona is characterised by a centralised water management model, in which decision-making authority and infrastructure operation are concentrated within a unified institutional framework. Melbourne, by contrast, operates under a decentralised, multi-level governance system, where responsibilities are distributed across multiple institutions, scales and actors. This unprecedented comparison allows researchers to isolate how a city’s institutional and organisational structure influences the design, acceptance and ultimate success of economic incentives aimed at conserving riverine and urban ecosystems.

The technical significance of this comparative design should not be underestimated. PES schemes do not operate in a vacuum; their effectiveness depends on who holds the legal authority to contract payments, how monitoring and verification of ecosystem outcomes are organised, whether local communities trust the institutions administering the scheme, and how costs are passed through water tariffs or public budgets. A centralised system may be able to implement a catchment-wide payment scheme quickly and coherently, but it may struggle to capture local knowledge or secure community buy-in. A decentralised, multi-level system may be more adaptive and participatory, but it risks fragmentation, duplicated effort and gaps in accountability. By studying both models in parallel, PES4URBANWATER aims to generate insights that transcend either city and speak to the structural conditions under which PES succeeds or fails.

Methodologically, the project integrates environmental and economic evaluations with public policy analysis, a multidisciplinary combination that reflects the reality that water governance sits at the intersection of hydrology, finance and politics. Central to this approach is the deployment of Water-Oriented Living Labs, or WOOLs—collaborative innovation spaces where public institutions, industry partners, researchers and local communities co-develop solutions together. These living labs are paired with innovative regulatory sandboxes, controlled environments in which new policy instruments and governance arrangements can be tested without the full weight of existing regulation, allowing experimentation with PES designs before they are scaled up.

The knowledge generated through these labs and sandboxes will be translated into strategic recommendations and decision support tools for policymakers, water authorities, water utility companies and other key stakeholders. Crucially, the project’s designers have emphasised transferability: the suite of tools is intended to guide urban planners, managers and policymakers in any major city worldwide, not only in the two study cities. In an era when climate change is stressing water systems from Cape Town to Chennai, from Sydney to São Paulo, a framework that can be adapted across institutional contexts could prove far more valuable than findings locked to a single governance model.

The project’s ambitions also extend to the global policy agenda. PES4URBANWATER is explicitly designed to align with and directly support major frameworks, including the EU Biodiversity Strategy for 2030, the European Green Deal and the United Nations Sustainable Development Goals. Each of these agendas calls for scaling up nature-based solutions and ensuring that the transition to sustainability is just and inclusive, and each recognises that healthy freshwater ecosystems underpin everything from biodiversity to public health to economic productivity. By demonstrating how economic incentives for ecosystem services can be structured equitably, the project seeks to provide a practical bridge between high-level policy commitments and the messy, contested realities of urban water management on the ground.

For the cities involved, the stakes are immediate and concrete. Barcelona faces recurring drought pressure on its Mediterranean water supply, while Melbourne contends with the hydrological volatility of a climate that swings between bushfire and flood. Both cities have invested heavily in alternative water sources, integrated urban water management and community engagement, making them natural laboratories for testing whether PES can complement hard infrastructure with investments in the living systems that regulate water naturally. If the project succeeds in showing that well-designed payment schemes can simultaneously improve water quality, protect resources, support climate adaptation and distribute costs fairly, it could reshape how cities around the world finance their relationship with the ecosystems they depend upon—moving urban water governance toward models that are more effective, more inclusive and grounded in evidence rather than ideology.

Subject of Research: Payment for Ecosystem Services schemes for equitable and resilient urban water management

Article Title: PES4URBANWATER drives fairer, more sustainable and resilient urban water management

Article References: PES4URBANWATER drives fairer, more sustainable and resilient urban water management. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: PES4URBANWATER, payment for ecosystem services, urban water management, water governance, Barcelona, Melbourne, distributive justice, climate change adaptation, Water-Oriented Living Labs, Horizon Europe, Marie Skłodowska-Curie Actions, water quality

The research, led by Associate Professor Mohammad Javad Koohsari of the Urban Design Science for Health Laboratory at the Japan Advanced Institute of Science and Technology (JAIST) together with Professor Koichiro Oka of the Faculty of Sport Sciences at Waseda University, examined the ethical properties of advice generated by ChatGPT for modifying built environments to support human health. The study was made available online on August 10, 2026, and will be published in Volume 27 of the journal Developments in the Built Environment on October 1, 2026. According to the researchers, it is the first investigation anywhere in the world to subject LLM-generated advisory text on urban design and health to a structured ethical audit.

The methodological design was deliberately rigorous. The team framed the evaluation around six well-established pathways through which the built environment shapes health: physical activity, dietary intake, social interaction, air pollution, traffic safety and crime, and noise. They then constructed 18 distinct prompts. Twelve of these described scenarios in higher-income and lower-income neighborhoods, while six described mixed-income neighborhoods operating under an explicit budget constraint, a condition that forces trade-offs and therefore exposes how a model distributes scarce resources. Each prompt was run ten times, yielding 180 separate responses for analysis.

Every response was then scored against four ethical criteria drawn from established frameworks in professional ethics: non-maleficence, meaning the avoidance of harm; distributive justice, meaning fair treatment of disadvantaged neighborhoods; collective participation, meaning recognition that communities should be involved in decisions affecting them; and transparent oversight, meaning acknowledgment that human judgment and institutional processes must govern the final outcome. Two co-authors independently coded all 180 answers, providing a check on subjective interpretation. This content-analysis approach converts the vague intuition that an AI answer “seems fine” into measurable, comparable evidence.

The headline result concerns harm avoidance. Non-maleficence was satisfied in all 180 responses, meaning that across every health pathway, income context, and budget condition, the model never clearly recommended a harmful or unsafe built environment change. It did not, for example, propose designs that would plausibly increase pedestrian injury risk or degrade air quality in ways that endanger residents. For a technology often criticized for confident errors, this baseline of safety in the urban design domain is a meaningful finding, suggesting that widely available models have absorbed at least the most fundamental professional conventions about what constitutes dangerous advice.

Distributive justice performed nearly as well. Of the 120 evaluable units, 110, or 91.7 percent, satisfied the criterion, indicating that lower-income neighborhood contexts were rarely handed systematically weaker proposals than their wealthier counterparts. In other words, when the model was asked how to make a disadvantaged neighborhood healthier through changes to walkability, land use, or public space, it generally produced recommendations of comparable quality and ambition. This matters because algorithmic systems have repeatedly been shown elsewhere to encode or amplify socioeconomic bias, and a failure of distributive fairness in urban planning advice could quietly entrench health inequalities.

Where the model faltered was on the procedural dimensions of ethical practice. Collective participation appeared in only 109 of 180 answers, or 60.6 percent, meaning that in nearly four out of ten cases the advice failed to mention that residents and communities should have a voice in shaping their own environments. Transparent oversight fared somewhat better but still fell short, appearing in 136 of 180 answers, or 75.6 percent. These gaps are significant because urban design for health is not merely a technical optimization problem; the legitimacy of a plan depends on how decisions are made, who is consulted, and how uncertainty and accountability are handled.

The differences became especially pronounced when the model faced constrained resources. In the mixed-income prompts that included a budget limitation, collective participation appeared in just 21 of 60 answers, or 35.0 percent, and transparent oversight in 28 of 60 answers, or 46.7 percent. By comparison, the same criteria were present in 73.3 percent and 90.0 percent of answers respectively in the prompt set without budget constraints. The pattern suggests that when forced to prioritize, the model defaults to a technocratic mode, allocating funds and selecting interventions while dropping the language of community engagement and human oversight. This is precisely the scenario in which procedural ethics matters most, since budget-driven prioritization determines which neighborhoods receive health-supporting investment and which are left behind.

“Our findings show that ethical urban design for health depends not only on what physical changes are proposed, but also on how decisions are made, who is involved, and how uncertainty and human oversight are addressed,” Dr. Koohsari said. The statement captures the study’s central conceptual contribution: evaluating AI advice solely on the plausibility of its physical recommendations misses half the ethical picture. A model can propose technically sound bus lanes, parks, and pedestrian improvements while remaining silent on the participatory and institutional processes that determine whether those proposals serve residents equitably.

The practical implications are nuanced rather than dismissive. The authors suggest that LLM-generated advice can serve as a useful initial input for urban designers, planners, and public health professionals brainstorming health-supportive changes to streets, public spaces, transportation infrastructure, land use, and greenspaces. The consistency of harm avoidance and the near-uniform distributive fairness indicate that such tools are unlikely to steer users toward obviously dangerous or inequitable proposals. However, the study is emphatic that these outputs should not replace professional judgment or genuine community participation, particularly when limited budgets require prioritization among competing needs. The procedural gaps identified in the research are exactly the areas where human deliberation, local knowledge, and democratic accountability cannot be delegated to a text generator.

“With appropriate safeguards, LLMs could support more health-informed urban design while ensuring that important decisions remain grounded in professional expertise, community participation, and institutional processes,” Dr. Koohsari concludes. As cities worldwide grapple with aging infrastructure, health inequities, and the pressure to adopt AI tools for efficiency, this study provides a template for what responsible adoption should look like: audit the outputs against explicit ethical criteria, watch closely for procedural failures under resource constraints, and treat the model as a drafting assistant rather than an ethical adviser. The technology, it turns out, has learned what not to propose; whether it has learned how decisions ought to be made is another question entirely, and for now the answer must remain with people.

Subject of Research: Ethical assessment of large language model-generated advice for health-oriented urban design

Article Title: AI and urban design for health: Are large language models ethical advisers?

Article References: AI and urban design for health: Are large language models ethical advisers?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: large language models, urban design, public health, ChatGPT, built environment, research ethics, distributive justice, community participation, urban planning, AI ethics, health equity, Japan

The research, conducted by Valentina Lucia La Rosa, Maria Luisa Indiana, Emanuela Borzì, Daniela Pirone, Elisabetta Sagone, Elena Commodari, and Alessandra Geraci at the University of Catania, builds on a well-established tradition in developmental psychology but adds a crucial cognitive twist. Earlier work had shown that children attribute fair and unfair distributions differently depending on the perceived gender of the distributor, yet comparatively little attention had been paid to the mental structures, known as schemas, that make such attributions possible. Gender schemas are organized knowledge structures that guide how children process, interpret, and remember gender-relevant information, and understanding when children first deploy them to encode social behavior is central to tracing the developmental origins of bias.

The team tested 160 typically developing children divided into four equal age groups: toddlers aged 2.5 years, preschoolers aged 3.8 years, kindergartners aged 5, and school-age children aged 8. Each child watched brief familiarization events in which a distributor, hidden behind a gray box, either gave one apple to each of two receivers, a cow and a pig, or handed both apples to a single receiver. Immediately afterward, the experimenter presented two schematic drawings, one male and one female, and asked the child to identify the distributor by picking up the correct picture. The position of the pictures was counterbalanced, the order of fair and unfair events was alternated across participants, and a manipulation check with 50 university students confirmed that the schematic figures were unambiguously recognized as male and female with 100 percent accuracy.

The results traced a non-linear developmental trajectory that surprised no one more than the researchers’ own carefully calibrated hypotheses. At 2.5 years, children chose the male and female figures at chance levels for both fair and unfair distributions, exactly as predicted by the literature on pictorial competence. Infants younger than three often treat pictures as objects to be touched and grasped rather than symbols that stand for something else, and the ability to hold both the physical properties of an image and its abstract referential meaning in mind simultaneously, what psychologists call dual representation, emerges only gradually. Without that symbolic foundation, the youngest participants simply could not map a schematic figure onto a real-world gender category, and their choices therefore revealed no gender-based pattern at all.

By 3.8 years, however, the picture changed dramatically. Seventy percent of children in this age group selected the male figure after watching a fair distribution, a statistically significant deviation from chance with a medium effect size, while their choices remained at chance after unfair events. This is the signature of what the researchers define as gender bias: a systematic tendency to attribute positive social behaviors preferentially to one’s own gender group, reflecting in-group favoritism without necessarily implying a negative evaluation of the out-group. The pattern was driven almost entirely by boys, 81.8 percent of whom attributed fair distributions to the male figure, while girls of the same age showed no significant tendency in either direction. According to Social Identity Development Theory, this asymmetry makes sense: in-group favoritism emerges as children consolidate a positive sense of group membership, and its strength depends on how salient and self-defining that group has become. For boys approaching their fourth birthday, gender may already function as a highly salient social category.

At age 5, the pattern flipped in a theoretically meaningful way. Children no longer associated the male figure with fair behavior; instead, 67.5 percent of them attributed unfair distributions to the male figure, again a significant departure from chance. This qualitative shift coincides with what decades of research identify as the developmental peak of gender stereotype rigidity, spanning roughly ages 5 to 7. During this window, children behave as what Martin and Ruble famously called gender detectives, diligently searching their environment for stereotype-consistent information and consolidating it into increasingly rigid expectations. Developmental Intergroup Theory predicts precisely this outcome: as gender becomes an ever more salient dimension of social life, children encode stereotype-consistent information with growing intensity, and here that intensity manifested as the association of men with dominant, inequitable behavior.

The most articulated pattern emerged among 8-year-old girls, who simultaneously attributed fair distributions to the female figure, at 71.4 percent, and unfair distributions to the male figure, at 78.6 percent. This combination of in-group favoritism and out-group negativity meets the study’s operational definition of gender prejudice, a qualitatively different construct from mere bias. Male 8-year-olds, by contrast, showed no significant gender-based pattern in either condition. The researchers suggest that girls at this age may have developed heightened sensitivity to gender-based social hierarchies, motivating a reactive intergroup stance in which protecting the in-group and devaluing the out-group become two sides of the same coin. Taken together, the findings sketch a trajectory in which boys display earlier but less differentiated in-group favoritism, while girls develop a later but more elaborated pattern that integrates group protection with out-group criticism.

The authors are careful to frame these results within a biosocial model rather than a simple nature-versus-nurture debate. An evolved sensitivity to group membership may provide the initial scaffold, but the direction of children’s attributions is unmistakably shaped by experience. From their earliest years, children observe that caregiving and daily resource allocation are unequally distributed across genders, and these accumulated observations likely feed the early association between the male figure and prosocial or dominant behavior. Crucially, the researchers emphasize that the attribution patterns observed here are not fixed developmental outcomes. Because they emerge from socialization, they remain modifiable: intervention research consistently shows that exposure to counter-stereotypical role models, such as female leaders and male caregivers in children’s stories, can attenuate gender bias even at preschool age.

The study does carry important boundary conditions. The sample consisted exclusively of White children from a single Italian region with limited socioeconomic diversity, so the observed patterns cannot be assumed to generalize to populations where gender norms and expectations about distributive fairness differ substantially. The use of highly schematic figures, while useful for isolating gender as the sole variable, reduces ecological validity, since real-world gender perception draws on a rich constellation of facial, vocal, and behavioral cues. Moreover, the forced-choice paradigm measures attribution behavior without directly observing the underlying schemas, and the authors call for future work pairing the task with independent assessments of gender schema knowledge, culturally diverse samples, longitudinal designs, and richer stimuli such as videos of dynamic social interactions.

Even with these caveats, the practical implications are difficult to overstate. The window in which gender schemas first begin to shape social reasoning opens before children turn four, long before formal schooling typically addresses equity in any systematic way. The findings argue for early childhood settings, nurseries, kindergartens, and caregiving environments, to actively promote counter-stereotypical representations of competence and fairness, particularly around resource sharing and leadership, rather than waiting for rigid prejudice to consolidate in middle childhood. Gender bias, the authors conclude, is not an inevitable consequence of development; it is a learned pattern, and what is learned early can be unlearned before it hardens. In a world where gender inequality continues to fuel conflict and injustice, the humble apples of a nursery-school experiment may mark one of the earliest and most promising points of intervention.

Subject of Research: The developmental emergence of gender schemas and gender bias in children's attribution of fair and unfair distributive actions.

Article Title: The Perception of Schemas and Gender Bias in the Attribution of Distributive Actions

Article References: La Rosa, V. L., Indiana, M. L., Borzì, E., Pirone, D., Sagone, E., Commodari, E., & Geraci, A. (2026). The Perception of Schemas and Gender Bias in the Attribution of Distributive Actions. International Journal of Early Childhood. https://doi.org/10.1007/s13158-026-00539-4

Image Credits: AI Generated

DOI: 10.1007/s13158-026-00539-4

Keywords: gender bias, gender schemas, distributive justice, child development, fairness, social cognition, gender stereotypes, developmental psychology, in-group favoritism, early childhood education, prejudice, resource distribution