Technical Mediation and Human Presence: A Study on Policy Evolution and Development Pathways of Future Communities

Abstract

As an advanced form of community development, Future Communities (Weilai Shequ) is a policy-led urban initiative launched in Zhejiang, China, that prioritizes human-centered development. However, it is currently confronted with an inherent contradiction: the expansion of technological rationality is encroaching upon humanistic values. Centering on the core “technology–human” relationship, this study is dedicated to exploring development measures for Future Community that synergistically integrate technological empowerment and humanistic care. Using natural language processing techniques (LDA topic modeling), we conducted an exploration and analysis of the thematic characteristics and evolution of 40 policy documents related to future communities issued by the central and local governments of China from 2014 to 2024. The study identifies six core topics: Quality Enhancement, Technical Foundation, Intelligent Operations and Maintenance, Green and Low-Carbon, All-Age Friendliness, and Community Services. Analysis revealed that each theme embodies a dual connotation of both technological and humanistic dimensions. Furthermore, the study revealed that the evolution of policy semantics follows a three-stage developmental pattern: technology dominance and nascent human-centered values; human-centered rise and technology empowerment; and human-centered deepening and technological embeddedness. Based on the above findings, and grounded in a phenomenological perspective, this study integrates Alexander’s human-centered architectural philosophy with Ihde’s theory of technological mediation to propose a future community construction pathway jointly driven by “technological mediation” and “human presence.” Theoretically, this research transcends the binary narrative of technology versus humanism. In practice, it provides policymakers with tools to avoid technological pitfalls. It establishes fundamental principles for planners and designers to implement humanistic values, ultimately aiming to realize, at the community level, the vision of technology serving humanity’s aspiration for a better life.

1. Introduction

1.1. Background and Issues

After experiencing rapid urbanization, high-density development under residential commodification, and the “standard-compliant” construction model, the Chinese community in the 21st century has entered a new era characterized by digitalization and intelligence [1,2]. Information technologies, such as artificial intelligence and digital twins, are profoundly reshaping social operational modes, governance models, and residents’ lifestyles [3,4,5]. However, as technology becomes deeply embedded in this process, its instrumental rationality tends toward overexpansion, leading to the risk of marginalizing the community’s humanistic values [6,7,8]. Current community development policies exhibit excessive reliance on technocratic standards, characterized by rigid adherence to quantitative indicators while neglecting responses to residents’ genuine living needs [9]. For example, under inflexible regulations and high floor-area-ratio development models, spatial design often degenerates into cold data outputs [10]: centralized lawns that meet green space ratios but prohibit access essentially result in the waste of public space and the loss of social value; monotonous building layouts formed solely to comply with sunlight spacing requirements sacrifice the affinity of places and the sense of community belonging, which may undermine social cohesion in the long run. Meanwhile, the standardized promotion of intelligent systems is creating new forms of social exclusion [11]. While facial recognition access control improves management efficiency, it inadvertently eliminates the social function of traditional guard posts as community information hubs [12]; when community services are entirely moved online, a significant proportion of elderly residents are excluded from the service system. This not only widens the digital divide but may also intensify intergenerational conflicts, posing serious challenges to social governance [13].

These phenomena profoundly reveal the inherent tension between technological efficiency and human-centered values. Against this backdrop, the “Future Community,” as a development model that prioritizes humanistic care while deeply integrating technological innovation, requires in-depth research. Such research should transcend simple technological application or humanistic criticism and instead explore a new community development path in which “technological mediation” and “human presence” synergistically reinforce each other. This holds crucial theoretical and practical significance for the development of sustainable, high-quality human settlements.

1.2. Review of Literature and Research Gaps

Policies serve as a key lever and actionable framework for guiding the development of future communities and balancing technological applications with human-centric values [14]. However, existing research on Future Community policies predominantly focuses on qualitative analyses, such as conceptual interpretations [15]; descriptions of practical cases [16,17,18], technological applications [19,20]; and community service and governance models [21,22,23]. Current studies have not adequately addressed the complex interplay between technology and human-centric values within normative policies on future communities, and research on reflecting, balancing, and guiding the “technology–human” relationship remains insufficient.

2. Data and Methods

2.1. Research Method

The Latent Dirichlet Allocation (LDA) is a generative probabilistic model that treats texts as “topic mixtures” [24]. By employing backward reasoning, it automatically discovers hidden thematic structures from large volumes of text and reveals the focal points of each piece [25,26]. Currently, in policy text analysis within the architectural discipline, a unique application framework has been established [27]. Its core lies in using unsupervised learning to uncover latent semantic structures in policy texts, providing data support for policy analysis, evaluation, and implementation pathways [28]. Specific applications include identifying thematic distributions and mechanisms in policy texts, quantifying topic probability distributions across different policy domains, and revealing thematic correlations and logical connections between policies [29]. Through temporal slice analysis, it examines policy evolution and trend predictions, revealing dynamic patterns in policy themes [30]. When combined with sentiment analysis, it quantifies public feedback on policies, facilitating the evaluation and optimization of effectiveness [31].

This study introduces the Latent Dirichlet Allocation (LDA) topic model into Future Community policy research. Starting with the semantic analysis of domestic policy texts, it conducts quantitative analysis on core themes, structural characteristics, and evolutionary patterns of Future communities. The research examines how these communities reconcile and resolve inherent tensions between technological advancements and humanistic values, offering new insights into understanding policy orientations and evaluating policy effectiveness. Furthermore, it proposes actionable and balanced recommendations for developing Future Community construction pathways.

2.2. Data Sources and Cleaning

To accurately explore the development trends of Future Communities in China, this study screened domestic community policies through the following criteria:

• Temporal Scope: Policies published via official Chinese government channels between January 2014 and December 2024;
• Document Selection Criteria:
  • Inclusion: current effective notices and guidelines with titles explicitly containing Community, Future Community, Urban planning, or Residential area, etc.;
  • Exclusion: approvals, meeting briefings, and forwarded documents;
  • Screening Process: The research team selected the policies through information retrieval and manual review (prioritizing those with strong guidance significance and high representativeness based on existing studies). Strong Guidance Significance: Defined as clear, objective criteria, either “national-level authority” or “local pioneering initiatives adopted by higher-level policies” (for example, Shanghai 15-Minute Community Life Circle Planning Guidelines); High Representativeness: Policies that are frequently cited or used as models in the policy documents of other regions (for example, Zhejiang Province’s Future Community Guidelines have influenced subsequent policies in multiple provinces).
• This yielded 40 policy samples comprising:
  • Types: Planning guidelines, technical standards, construction manuals;
  • Administrative Levels:
    • National-level: 14 documents;
    • Local-level: 26 documents (see

      Table 1. Partial list of community policies.

      Serial	Enactment Date	Title
      1	May 2014	‘Guidelines for the Construction of Smart Communities (Trial Version)’
      2	January 2024	‘Design Guidelines for Embedded Services in Urban Communities (Trial Version)’
      3	January 2022	‘Plan for the Construction of Urban and Rural Community Service Systems in the 14th Five-Year Plan’
      4	July 2021	‘Technical Guidelines for the Planning of Community Living Circles’
      5	December 2021	‘Construction Guidelines for Complete Residential Communities’
      6	September 2019	‘Urban Design Guidelines for New Residential Communities in Tianjin’
      7	January 2020	‘Controlled Detailed Planning for the Starting Area of Hebei Xiong’an New Area’
      8	April 2023	‘Action Plan for Creating Green Complete Residential Communities in Hunan Province’
      9	June 2022	‘Construction Guidelines for Future Park Communities in Chengdu’
      10	July 2024	‘Guidelines for the Promotion of Future Community Construction on a Wider Scale’
      11	May 2022	‘Guide for the Pilot Construction of Low-Carbon Communities’
      12	February 2019	‘Work Plan for Pilot Construction of Future Communities in Zhejiang Province’
      13	December 2020	‘Standards for the Construction of Child-Friendly Communities in China’
      14	July 2022	‘Construction Guidelines for Near-Zero Carbon Communities’
      15	October 2024	‘Technical Guidelines for Good Communities’

      Note: Due to space limitations, only a portion of the 40 policies selected for the research are listed in the above table. The complete policy data of this study can be found in Appendix A.

      for the whole dataset).

To ensure research data integrity and address heterogeneity, the following cleaning strategies were applied to the 40 policy texts (Figure 1):

• Stop Word Removal and Standardization:
  • Utilized the HIT Stop Words List (Harbin Institute of Technology) and a custom stop word list (e.g., own, village, article, urban–rural, industry, development).
  • Performed cross-regional term alignment: Unified localized phrases like Zhejiang’s and Chengdu’s “Nine Major Scenes” under the standardized label “Scenes”.
• TF-IDF Keyword Extraction:
  • Applied the TF-IDF algorithm to identify high-frequency terms
  • Manually validated core concepts (e.g., public services, embedded, elder care, sharing)
  • The total keyword frequency count has been finalized at 11,728
• Policy Version Tagging:
  • Marked the key version changes (2014–2024) based on the iterative nature of the policies (e.g., Documented revisions of Shanghai 15-Minute Community Life Circle Planning Guidelines).

2.3. Topic Modeling Construction

This study employs the LDA model proposed by Blei et al. For mining topics in policy text. To ensure the robustness of policy topics, a three-stage optimization is implemented as follows:

• Iteration Calibration

Preliminary experiments confirmed stabilized perplexity at ≥2000 iterations (Δ perplexity < 5%).

Parameter set: n_iter = 2000.

2.

Hyperparameter Tuning

Adjusted for short-text characteristics of policy documents:

α = 0.1

β = 0.01

“We performed topic modeling on the policy corpus using Latent Dirichlet Allocation (LDA). After testing the default parameters (α = β = 0.1), we adjusted to a conservative document-topic prior (α = 0.1) and a sparser topic-word prior (β = 0.01), ultimately obtaining more coherent and interpretable topics with lower keyword overlap, which also correspond well to established policy focus areas.”

3.

Validation Framework

Established a perplexity-coherence verification framework.

Balanced model, Goodness of Fit, and semantic rationality through manual validation.

Model Optimization Findings:

In this model, perplexity remains at a relatively low level, and coherence peaks at 6 or 10 topics. Visualization shows the following:

Larger bubble size indicates a higher topic probability distribution; greater distance between bubbles reflects lower similarity between topics.

At K = 10: topic overlap occurs, uneven probability distribution, suboptimal classification efficacy;

At K = 6: quantitative metrics: perplexity = 42.3, coherence = 0.375, balanced model fitness and semantic coherence, uniform probability distribution, minimal topic similarity.

Thus, we determine K = 6 as the optimal topic number for this policy model. (Figure 2).

3. Deconstructing Community Policy Discourse

3.1. Policy Topic Identification and Labeling

The LDA topic model analyzed 40 policy texts, identifying six core topics (Topics 1–6). Labels were validated through semantic weight analysis and expert consensus (Kappa = 0.83, four architecture-planning specialists) (

Table 2. LDA topic recognition and keyword distribution.

Topic Number	Topic Naming	Key Phrase Group (Fifteen Items)
Topic 1	Quality Enhancement	Setting 0.019, Element 0.019, Configuration 0.010, Indicator 0.010, Space 0.010, Facility 0.007, Planning 0.007, Construction 0.007, Minute 0.006, Layout 0.005, Community 0.034, Service 0.023, Life Circles 0.009, Demand 0.005, Quality 0.004
Topic 2	Technical Foundation	Facility 0.022, Residential area 0.013, Land use 0.012, Supporting facility 0.007, Green space 0.005, Roads 0.005, Access point 0.004, Street 0.005, Pedestrian 0.006, Scale 0.006, Area 0.007, Planning 0.008, Function 0.005, Public 0.011, Activity 0.008
Topic 3	Intelligent Operations and Maintenance	Wisdom 0.007, System 0.005, Platform 0.003, Technology 0.003, Data 0.003, Indicator 0.004, Innovation 0.004, Management 0.006, Construction 0.018, Ecology 0.005, Community 0.042, Future 0.006, Culture 0.006, Sharing 0.003, Scenario 0.003
Topic 4	Green and Low-Carbon	Construction 0.054, Low-carbon 0.037, Pilot 0.036, Emission 0.034, Zero-carbon 0.021, Standard 0.013, Energy 0.008, Transformation 0.009, Building 0.008, Emission reduction 0.005, New energy 0.004, Accounting 0.007, Demonstration 0.005, Community 0.064, Green 0.014
Topic 5	All-Age Friendliness	Embedded 0.012, Facilities 0.011, Service facilities 0.010, Shelter 0.004, Resilience 0.004, Operation 0.004, Coordination 0.004, Assurance 0.005, Community 0.050, Services 0.020, Children 0.006, Elderly care 0.005, Infants 0.004, Place 0.005, Demand 0.009
Topic 6	Community Services	Construction 0.024, Facilities 0.007, Promotion 0.007, Governance 0.005, Systematization 0.005, Improvement 0.006, Mechanism 0.006, Wisdom 0.005, Resources 0.003, Community 0.066, Participation 0.004, Service 0.024, Community Service 0.009, Public service 0.004, Grassroots 0.004

):

• Topic 1: Quality Enhancement;
• Topic 2: Technical Foundation;
• Topic 3: Intelligent Operations and Maintenance;
• Topic 4: Green and Low-Carbon;
• Topic 5: All-Age Friendliness;
• Topic 6: Community Services.

Topic 1: Quality Enhancement

This semantic nexus centers on community and services, with life circles, needs, and quality forming interconnected nodes. The keywords reflect the government’s spatial planning imperatives for the “15-Minute Community Life Circles”, aligning with the value orientation of human settlement optimization articulated in the Ministry of Construction Guidelines for Complete Residential Communities and Action Plan for 15-Minute Community Life Circle in Shanghai 2024.

Topic 2: Technical Foundation

This topic focuses on high-weight terms, including Facilities, Land Use, and Planning, which reflect technical norms for constructing community physical spaces. Key terms such as Roads, Green spaces, and Access points represent infrastructure planning elements. These map to the technical substrate characteristics of physical space design in architecture, signaling a mandatory technical standard system for community development.

Topic 3: Intelligent Operations and Maintenance

This topic centers on technology-driven lexemes—smart, systematic, data-centric—highlighting the dynamic operational nature of construction and management. Keywords such as “Platform” and “Scenes” demonstrate the systemic integration of digital technologies into community operations, aligning with technical iteration imperatives under the Smart Cities framework.

Topic 4: Green and Low-Carbon Development

This cluster exhibits significant convergence around domain-specific terminology—Low-carbon, Zero-carbon, and New energy. Keywords such as Transformation, Emission Reduction, and Accounting underscore the objectives of eco-community development, signifying sectoral responsiveness to the Dual Carbon Goals.

Topic 5: All-Age Friendliness

This topic addresses the lifespan-differentiated needs of residents, with separate specifications for Children, Elderly care, and Infants, outlining spatial and functional requirements for distinct groups. Terms such as Embedded, Coordination, and Assurance indicate the precise allocation of community resources. Through words such as coordinating and articulating, it reflects the fairness of resource allocation and the resident participation mechanism.

Topic 6: Community Service

Focusing on community governance and resource integration, keywords such as Community, Construction, Promotion, and Mechanism emphasize organizational and coordination logic in community operations. Governance, Systematization, and Improvement denote institutional refinement of management protocols, while Facilities and Resources reflect the utilization of external resources by the community.

3.2. Analysis of Policy Topic Characteristics

Based on the topics’ connotations and keyword distributions, it is evident that each topic encompasses both technological and humanistic elements. Technological elements primarily refer to specific methods, tools, and implementation pathways, while humanistic elements focus on human needs, values, and agency. Through a comparative analysis of the semantic weights across topics, the proportional relationships and characteristic differences between these two types of elements in different topics can be more precisely captured. It clearly depicts the tension and integration between technical rationality and humanistic value in policy discourse (Figure 3):

Topic 1: The technological and humanistic semantic weights are 0.060 and 0.115, respectively. This distribution suggests a greater emphasis on humanistic concerns. High-frequency keywords such as Life circles, Needs, and Quality reflect a shift in policy discourse from the physical optimization of space to the pursuit of spatial quality, signaling that the focus of community development has deepened from physical hardware improvements to attention toward residents’ agency and spiritual needs.

Topic 2: The technological semantic weight is 0.106, far exceeding the humanistic weight of 0.019. This numerical gap demonstrates the dominance of technological elements in this topic. High-frequency terms, such as Land use, Supporting facilities, and Green space, reflect the salient representation of technical indicators in issues like spatial planning and public facility configuration at the semantic level. This distribution suggests that policy discourse under this topic is highly focused on the systematic planning of physical space.

Topic 3: The technological and humanistic semantic weights are 0.067 and 0.051, respectively, showing a relatively balanced distribution. This indicates that both types of elements contribute equally at the semantic level. In this topic, technological means such as Smart, Platform, and Data coexist with humanistic appeals such as Ecology, Culture, and Sharing, reflecting synergy and balance between technological applications and humanistic values. This equilibrium not only illustrates how technology actively responds to and integrates humanistic needs in practice but also marks a transition in technology’s role in community development from one of instrumental dominance to one of collaborative support.

Topic 4: The technological semantic weight (0.241) is significantly higher than the humanistic weight—more than three times that of the latter—demonstrating a clear technologically dominant characteristic. However, high-frequency terms in this topic, such as Low-carbon, Green, and Emission reduction, reflect how low-carbon technologies, new energy applications, and others are centered on enhancing environmental sustainability and public health. Here, technology serves not only to achieve efficiency gains but also carries a profound ethical orientation and humanistic concern. Its fundamental aim is to translate humanistic values into practical pathways that can be implemented at the community level through engineering and systematic innovation.

Topic 5: Through keywords such as Children, Elderly care, and Resilience, this topic achieves a deepening and expansion of humanistic across vertical dimensions. These keywords encompass all age groups, from youth to old age, and diverse social contexts, reflecting the widespread adoption of humanistic approaches to multidimensional scenarios. The humanistic semantic weight in this topic reaches 0.099, exceeding the technological weight (0.057) by 73.7%. A gap of this magnitude indicates a strengthening trend of humanistic elements in this semantic domain.

Topic 6: The humanistic semantic weight (0.111) is significantly higher than the technological weight (0.068), with a difference of 0.043, highlighting the central role of humanistic elements in this topic. High-frequency terms such as Participation and Governance not only reflect the emphasis on public agency in policy semantics but also actively promote a role transformation: the public is shifting from passive service recipients to active decision-makers and co-builders of governance. Such keywords signal an evolution of community governance models toward greater inclusivity and empowerment.

In summary, Topics 2, 3, and 4 demonstrate a three-stage gradient evolution of technological elements in policy semantics: from the “construction of a technological foundation” in Topic 2, which emphasizes infrastructure and spatial resource allocation, to the “technology-humanistic integration” in Topic 3, which balances smart platforms with ecological and cultural elements, and finally to the “humanization of technological values” in Topic 4, which is oriented toward low-carbon and health goals. This evolution indicates that policy has transitioned from a traditional “technology-first” single linear mindset to one that regards technology as an active element embedded within community systems. The optimization logic no longer revolves solely around the self-iteration of technology, but rather emphasizes in-depth interaction and symbiosis between technology and multiple dimensions such as community governance, culture, environment, and resident well-being.

Correspondingly, Topics 1, 5, and 6 systematically present a deepening path of humanistic orientation: from spatial optimization aimed at quality improvement in Topic 1, to a care system covering all age groups and diverse scenes in Topic 5, and further to the construction of agency emphasizing public participation and co-governance in Topic 6. This path marks a transition in Future Community construction toward the higher-dimensional goal of “holistic human development” rather than merely “spatial construction”.

3.3. Policy Topics Evolution Analysis

Based on the document-topic probability matrix output by the LDA topic model for policy texts between 2014 and 2024, this study uses the six most significant topic probabilities and their dominant topics (max-topic) as analytical objects, identifying a significant value shift within China’s community policy discourse system (Figure 4 and Figure 5).

• 2014–2018: Technology Dominance and Nascent Human-Centered Values

Between 2014 and 2016, policy discourse was highly concentrated on the Technical Foundation (Topic 2, probability value of 0.88), primarily covering technical support elements such as infrastructure, land use allocation, and green space systems. The concept of Green and Low-Carbon (Topic 4) began to emerge in 2015, with its probability value rising to 0.23, indicating that under the impetus of new urbanization and sustainable development strategies, requirements such as ecological conservation, energy-saving renovations, and green building were gradually being integrated into community planning. This phase is primarily oriented toward building a technical foundation, with a focus on solidifying the hardware support system for community planning. A development trend toward informatization and low-carbon transition characterizes it.

From 2017 to 2018, significant structural shifts occurred in the policy topic. The probability of Green and Low-Carbon (Topic 4) further surged to 0.49, replacing the Technical Foundation (Topic 2, which fell to 0.23 in 2018) as the dominant topic, marking the deep embedding of ecological goals into the core of policy. Meanwhile, Community Services (Topic 6) experienced a short-term significant spike in 2017 (increasing by 0.99), and although it dropped back to 0.07 in 2018, it still revealed active policy exploration in the service domain. Quality Enhancement (Topic 1) also rose to 0.17 in 2018. The policy has clearly shifted from infrastructure construction to service optimization and innovation in governance mechanisms. Content began to emphasize soft service aspects such as convenience services, elder and child care, community healthcare, and cultural recreation, extending further into areas like quality of life, environmental comfort, and service refinement. This aimed to systematically address early shortcomings in service functions and comprehensively enhance residents’ living experience.

From the perspective of document-topic dominant distribution, texts in 2014 were highly concentrated on Topic 2, reflecting focused and coherent policy objectives. By 2018, texts were widely distributed across multiple topics (Topics 1 to 4), covering content such as Quality Enhancement, Technical Foundation, Intelligent Operations and Maintenance, Green and Low-Carbon. This shift from a “concentrated” to a “dispersed” thematic distribution clearly demonstrates that China’s community policies are evolving from a starting point of technical infrastructure toward an integrated development approach guided by ecological sustainability, centered on human experience, and implemented through systematic governance. This evolution not only reflects a semantic shift in values but also marks the transition of China’s community construction from an initial phase of “neighborhood development” to a new stage emphasizing holism and human-centeredness—that of “community placemaking.”

2.

2019–2021: Human-Centered Rise and Technology Empowerment

In 2019, the technology-related topic Intelligent Operations and Maintenance (Topic 3) dominated with a probability value of 0.54, reflecting a policy emphasis on the operation and maintenance of key technological infrastructures such as the Internet of Things, big data, and intelligent security systems. By 2020, the probability value for Technical Foundation (Topic 2) sharply declined to 0.02, while Intelligent Operations and Maintenance (Topic 3) and Green and Low-Carbon (Topic 4) remained at 0.32 and 0.01, respectively. This indicates that policy resources continued to be allocated to smart infrastructure operations, whose functions gradually evolved into a supportive role for service systems.

Meanwhile, human-centered topics significantly increased and gradually became dominant: the probability value for Community Services (Topic 6) jumped from 0.26 in 2019 to 0.65 in 2020 and remained stable at 0.64 in 2021. Quality Enhancement (Topic 1) also rose notably to 0.25, while All-Age Friendliness (Topic 5) began to emerge (0.02). This shift signifies a transition in policy focus from the mere “availability” of services to the pursuit of “quality,” with deepened attention to service refinement, environmental comfort, cultural connotation, and the comprehensive coverage and quality improvement of convenience, elder care, and medical services—highlighting a distinct “service turn.”

From the perspective of document-topic dominant distribution between 2019 and 2021, the semantic emphasis of policies clearly shifted from “technology empowerment” to “serving the people.” The thematic distribution was highly concentrated on Quality Enhancement (Topic 1), “Intelligent Operations and Maintenance (Topic 3), and Community Services (Topic 6). The consistently high prominence of Topic 6 is particularly critical, marking a substantive transition in policy semantics from early “infrastructure construction” to “service and human-centeredness.”

Overall, technology-related topics (2, 3, 4) showed a declining trend, while human-centered topics (1, 5, 6) continued to rise. The two appeared to be in contention within the policy semantic space. This ebb-and-flow pattern reflects a strategic reconfiguration of priorities, revealing an evolution in policymakers’ understanding: community modernization is no longer merely a technological “hardware” upgrade but also a “software” revolution concerning governance models and service effectiveness.

3.

2022–2024: Human-Centered Deepening and Technological Embeddedness

The period from 2022 to 2024 witnessed a structural deepening of human-centered values and a systematic shift in the role of technology within policy themes. Specifically, the weight of Community Services (Topic 6) decreased significantly from 0.76 in 2022 to 0.19 in 2024, while Quality Enhancement (Topic 1) also declined from 0.25 in 2021 to 0.09 in 2023. In contrast, All-Age Friendliness (Topic 5) rose rapidly, remaining elevated at 0.61 in 2024, establishing it as the core policy issue during this phase. This shift reflects a move away from generalized service provision and quality guidance toward refined and precise service design tailored to diverse age groups and populations, highlighting a policy orientation that emphasizes inclusivity and profound humanism.

On the technological dimension, Intelligent Operations and Maintenance (Topic 3) continued to decline gradually, registering 0.22 in 2022 and 0.17 in 2024. Technical Foundation (Topic 2) reemerged with a weight of 0.19, joining Green and Low-Carbon (Topic 4) in assuming supportive roles. Although technology-related topics collectively receded into a secondary position, they remained an essential foundational support system, continuously enabling the effective operation of community services and the realization of human-centered objectives.

From the perspective of document-topic dominant distribution, Topics 5 and 6 became the mainstream of the new policy discourse. Human-centered topics (Topics 1, 5, and 6) comprehensively surpassed technology-related topics (Topics 2, 3, and 4) in overall weighting. This stage marks not only the ascendancy of human-oriented approaches in policy semantics but also their systematic and structured in-depth development—the policy focus transitioned from “basic services” to “all-age friendliness,” reflecting a significant increase in the granularity and precision of care. Technology has shifted from a dominant force to an enabling tool that serves people. Overall, China’s community policy has formally entered a new stage centered on the “holistic development of people” as its fundamental goal.

4. Technical Mediation and Human Presence: Development Pathways for Future Communities

In summary, the analysis reveals a shift in two core thematic strands within policy evolution: the role of technology has moved from a unidirectional understanding as a tool to a relational perception as a mediator, while the status of humanistic values has transitioned from obscurity to presence. The tension between “technology and humanity” has consistently permeated the development of the field of architecture. C. Alexander proposed a solution rooted in the phenomenological tradition, while Don Ihde constructed a systematic theoretical framework for it from the perspective of the philosophy of technology.

4.1. Theoretical Foundation

In The Timeless Way of Building, Christopher Alexander asserts that the sole criterion for evaluating architectural quality lies in genuine human experience, rather than technical specifications or statistical data. By placing human feeling at the pinnacle of architectural judgment, he emphasizes that technological rationality detached from humanistic guidance becomes “lifeless”—a stance that directly challenges technocratic values. Alexander’s concept of “pattern language” serves as a pivotal tool for reconciling technology and humanism. Patterns do not address purely technical issues but rather “space-event” relationships. Taking the “window seat” pattern as an example, its essence lies not in the structural calculation of the windowsill, but in the human experience of “loving to sit at a window with light, a view, and a sense of enclosure.” This approach ensures that the design process always begins with human behavior and feeling, and that technical means are employed to fulfill these humanistic objectives. Alexander does not simplistically oppose technology; instead, he fundamentally questions the modern overemphasis on technical rationality, advocating for technology to assume a subordinate role in the service of humanity.

Don Ihde’s theory of technological mediation builds upon and deepens the ideas of C. Alexander, further emphasizing the mediating nature of technology and affirming the presence of human subjectivity within technological contexts. Ihde’s theory elaborates on the transformative relationship among humans, technology, and the world, positioning technology as a mediator that regulates the interaction between humans and the world [32,33,34]. He established a core framework consisting of four relations: Background, Alterity, Hermeneutic, and Embodiment (Background relationship: it constitutes the environment and atmosphere of our lives; Other relationship: it refers to technology becoming an independent “other” that requires interaction with; Interpretation relationship: technology is a text or symbol system that needs to be interpreted, and it “tells” us information about the world; Embodiment relationship: technology is “absorbed” into our bodily experiences and perceptions, becoming an extension of our bodies.), deconstructing the long-dominant notion of technological determinism [35]. The theory clarifies that whether technology serves as an operational environment, an existential other, a hermeneutic sign, or a bodily extension, its meaning fundamentally depends on human perception, interpretation, and needs—revealing technology’s inherent dependence on human subjectivity [36].

Both scholars reject the notion of technological neutrality, emphasizing instead how technology actively shapes human experience. Ihde provides a solid philosophical foundation for Alexander’s intuitive insights through phenomenological concepts such as “mediator” and “transformation of experiential structures.” While Alexander articulates the ideal relationship between technology and humans—where technology should recede into the background to serve a greater whole—Ihde systematizes this insight with his sophisticated human-technology relational model, establishing a universal philosophical framework applicable to all technologies. The integration of their theories provides a robust theoretical basis for understanding the synergistic relationship between “technological mediation” and “human presence” in future communities (

Table 3. Alexander’s relationship theory with Ihde: the deepening of thoughts and the correspondence with architectural dimensions.

Human- Technology Relations	Interpretation and Deepening of Alexander’s Thought	The Correspondence Between Ihde’s Relational Model and Architecture
Background	1. Expand the scope of analysis and reveal that “unnamed traits” rely on reliable and non-interfering technical backgrounds (such as temperature and humidity, clean air); 2. Shift the focus from “buildings” to “technical environment” and criticize the systemic flaws of the technological domination.	1. Technology is transformed into a continuously operating infrastructure or environmental conditions; 2. The physical entities of buildings and the supporting environment constitute the material foundation for the existence of buildings, providing stable support for human activities.
Alterity	1. Detailed critique of “lifeless” architecture: If architecture functions as an “alien other”, it will sever the connection between humans and the world. 2. Elevate the esthetic critique of “differently constructed” architecture to a critique of harmful intermediary relationships, applicable to technocratic governance or formalist design.	1. Technology is regarded as an “independent, opposing other”, especially the digital intelligent systems in architecture; 2. These systems have their own rules and life cycles, and their operation may not be in sync with user needs. The core is to provide efficient services.
Hermeneutic	1. Deepen the cognitive guiding role of “pattern language”: The architectural environment, like “text”, conveys information and guides behavior through its form; 2. Elevate “pattern language” from a design catalog to a phenomenological theory of spatial narrative.	1. Technology is “the medium for interpreting information and generating meaning”; 2. It helps humans understand the non-material needs of the environment (such as spirit, culture, and emotion), making the latent needs perceivable and operable.
Embodiment	1. Deepen the “anonymous trait” experience mechanism: Successful architectural elements seamlessly integrate with the human body and “retreat to the background of consciousness”; 2. Transform the overall judgment of “sensory alignment” into a precise description of “perceptual transparency”.	1. Pursuing the harmonious coexistence of technology and human sensory organs; 2. Technology, as a natural extension of human perception and action, realizes intuitive interaction, deepens environmental perception, and creates healthy and diverse architectural experiences.

).

4.2. Analysis of the Correlation Between Nine Major Scenes and the Core Framework

The essence of Future Communities lies in being a new paradigm for community development that is human-centered, technology-empowered, and focused on systemic reshaping. China’s Future Community initiative proposes the “Nine Major Scenes”—Future Neighborhood, Education, Entrepreneurship, Health, Transportation, Governance, Service, Low-Carbon, and Architecture—as the core guidance for construction. The use of the term “scenes” here transcends traditional static concepts such as functional zones or facility provision. It accurately captures the core feature of Future Communities: technology and humanity are not separated. However, they are coupled and co-evolving, reflecting a high degree of integration of the two core policy themes and the dual connotations of technical mediation and human presence within the Future Community concept.

The construction and implementation of the Nine Major Scenes should be approached from a four-dimensional core framework (Figure 6):

• Background: Built Environment;
• Alterity: Digital Technical Support;
• Hermeneutics: Need Response;
• Embodiment: Perceptual Experience.

Together, these form an organic whole that drives the development of Future Communities, propelling the scenes from blueprint to concrete community practice.

The Built Environment serves as the physical carrier of technical mediation, characterized by transparent embedding. It translates technical logic into perceptible spatial forms and acts as the physical foundation for scene implementation. Digital Technical Support acts as the explicit enabler of technical mediation, expanding the functional boundaries and service precision of the scenes through digital technology. Need Response constitutes the core link of human presence, focusing on residents’ diverse needs across the nine scenes and establishing meaningful connections between technological supply and humanistic demands. Perceptual Experience represents the ultimate goal of human presence in practice, emphasizing the connection residents form with the scenes through physical action and sensory interaction, thereby translating needs into concrete experiences (

Table 4. Correlation analysis of the nine scenes of future communities and the core framework.

	Future Neighborhood Scenes
B	Comprehensive service facilities: community service center, community affairs processing center, community living rooms, etc.; shared spaces: distributed outdoor social spaces, covered corridors, social restaurants, etc.; Diversified housing: commercial housing, affordable housing, public rental housing, co-living apartments, etc.; shared services platform: neighborhood swap stations, smart emergency supply lockers, etc.
A	Community digital interaction platform: online activity booking, neighborhood social apps, etc.; digital repository of the community.
H	Needs for intergenerational integration; needs for unplanned social encounters; needs for mutual support; Needs for cultural identity.
E	Community activities: cultural and historical collection activities, festival celebrations, etc.; daily interactions: casual conversations, strolls, and other routine activities, etc.; mutual aid experiences: neighborhood support initiatives, pet-related social experiences/activities facilitated by pets to promote interaction, etc.
	Future Education Scenes
B	Learning spaces: community libraries, kindergarten, primary and secondary school intergenerational learning areas, cross-generation workshops, etc.; Ecological experience spaces: wetland education gardens, insect observation walkways, etc.; Traditional cultural spaces: living heritage markets for intangible cultural heritage, folk craft workshops, etc.; Cultural memory carriers: community museums, etc.
A	AI-powered personalized learning platforms, VR immersive classrooms; remote education systems; visualized traditional craftsmanship networks.
H	Needs for lifelong learning across all ages; needs for boundary-free learning; needs for embodied cognition; needs for meaning construction; needs for technology domestication.
E	personalized learning; remote learning experiences; VR classroom experiences; community artisan craft experiences; digital detox and meditation experiences; children’s activities and interest development; customized course pushing, etc.
	Future Entrepreneurship Scenes
B	Core incubation carriers: makerspaces, incubation bases, sci-tech innovation labs, entrepreneurship service centers, etc.; shared workspaces: co-living apartments, modular reconfigurable offices and furniture, etc.; achievement demonstration spaces, etc.
A	Scientific research platforms; one-stop entrepreneurship service platforms; on-demand rental systems for experimental technical equipment: 3D printers, laser cutters, etc.; optimization technique of workstation allocation using spatial heatmaps.
H	Needs for flexible office arrangements; needs for cross-boundary collaboration; needs for low-cost startup; needs for risk resilience support; needs for resource connection; needs for community integration.
E	Flexible rental of workstations or meeting rooms; easy access to entrepreneurial resources and services; open and accessible entrepreneurship services, etc.
	Future Health Scenes
B	Fitness and exercise spaces: gymnasium, sports fields, intergenerational fitness zones, etc.; healthcare spaces: community health centers, daytime care centers, etc.; therapeutic environment spaces: healing landscape gardens, meditation trails, etc.; accessibility facilities: barrier-free pathways, all-age-friendly ramps, etc.
A	Smart medical wearables; online consultation systems; health data management platforms; data firewalls; real-time monitoring systems.
H	Needs for full-life-cycle health management; needs for data security assurance; Needs for non-medical health support; Needs for health equity realization; needs for life meaning enrichment.
E	Prevention-diagnosis-rehabilitation full-process care experience; non-medical rehabilitation experiences: spaces, landscapes, social interactions, etc.; age-appropriate motion-sensing games, etc.
	Future Transportation Scenes
B	Green travel networks: narrow streets and dense road network, multi-level greenways, charging piles, etc.; Transportation hub nodes: community micro-hubs, TOD mixed-use development, etc.; human-centered facilities: bike sharing, shaded rest waiting shelters, child-friendly zebra crossings, etc.
A	Smart parking systems; real-time bus scheduling apps; shared mobility platforms.
H	Needs for safety and resilience; needs for all-age inclusivity; needs for efficiency and convenience; needs for comfort experience; needs for community identity.
E	All-age safe travel assurance: barrier-free access for disabled individuals, etc.; green corridor and slow-traffic experiences; the convenient transfer experience of the community: walking, cycling, public transport, etc.
	Future Governance Scenes
B	Deliberation and consultation spaces: community meeting halls, shared lounges, online-offline discussion spaces, etc.; property management office; community security office, etc.
A	Digital governance platform; smart property management system: smart access control, parking systems, intelligent security monitoring, etc.; online deliberation platform; disconnection emergency response system.
H	Needs for transparent supervision; needs for cultural identity; needs for democratic participation; needs for flexible and efficient mechanisms; needs for co-construction, co-governance, and shared benefits.
E	Public affairs tracking: public fund flows, incident handling progress, etc.; smart steward experience; democratic participatory deliberation, etc.
	Future Service Scenes
B	Commercial facilities: banks, shopping malls, supermarkets, cafés, etc.; dining services: breakfast restaurants, community canteens, etc.; daily services: markets, postal services, repair shops, laundromats, pharmacies, etc.; Communications and home services: telecommunications service points, housekeeping service points, etc.
A	“Integrated Online Government Services” and online service platforms; all-in-one daily service APP; Digital business service platforms; Community group purchasing and e-commerce.
H	Needs for functional comprehensiveness; needs for diverse consumption scenarios; needs for cultural and creative expression; needs for payment inclusivity; needs for all-age inclusivity.
E	Leisure consumption experiences: shopping, watching shows, coffee, etc.; diverse payment experiences: cash, QR code, facial recognition, self-checkout, etc.; unmanned delivery experience, etc.
	Future Low-Carbon Scenes
B	Passive energy-saving housing; resource recycling facilities: waste sorting stations, rainwater harvesting gardens, greywater irrigation systems, etc.; low-carbon energy facilities: building-integrated photovoltaics, district energy stations, etc.; ecological resilience spaces: community agricultural greening, disaster prevention refuge lawns, sponge-type green space vertical greening, etc.
A	Environmental monitoring systems; equipment system performance testing; building intelligence; Energy-saving management systems.
H	Needs for ecological resilience; needs for all-age-friendly environments; needs for low-cost maintenance; needs for disaster emergency response; needs for cultural identity.
E	Green residential experience; local plant and crop experiences; ecological green space landscape experiences; daily leisure spaces with hidden emergency functions, etc.
	Future Architectural Scenes
B	spatial organization models: five-minute life circle units, mixed-use blocks, etc.; Community public spaces: green spaces and squares, community parks, multi-functional activity rooms, community development centers, public benefit activities spaces, etc.; green low-carbon buildings: energy-efficient buildings, prefabricated buildings, etc.
A	Geographic information systems and spatial analysis technology; Building Information Modeling (BIM); prefabricated construction technology; Smart construction site sensors and AI monitoring.
H	Needs for green ecology; needs for energy saving and safety; needs for comfort and convenience; needs for regional culture; needs for participation and social interaction.
E	Community planning and design VR/AR experience; community energy consumption simulation experience; comfortable living environment experience, etc.

B: Background—Built Environment, A: Alterity—Digital Technical Support, H: Hermeneutics—Needs Response, E: Embodiment—Perceptual Experience. This material is compiled based on the Zhejiang Province Pilot Work Plan for Future Communities Construction, the Planning Guidelines for Future Park Communities in Chengdu, as well as the top ten outstanding future park communities in Chengdu in 2023 (Blue Ribbon Future Park Community in Chengdu Eastern New District, Bai Luanwan Future Park Community in Jin J District, Fu R Future Park Community in Wu Hou District, “TOD + 5G” Future Park Community in Xin Jin District), and the outstanding cases of the fourth batch of future communities in Zhejiang Province for 2024 (Li Xian Future Community in Qu Zhou, Stadium Future Community in Huzhou, Fu Du Future Community in Zhoushan, Ling Shan Future Community in Lian Hu District).

).

From the perspective of the relationships within the four-dimensional framework, the built environment provides a context for digital technology; digital technology supplies the tools for Need Response; need response guides the direction for Perceptual Experience; and Perceptual Experience, in turn, informs the iterative optimization of the built environment.

4.3. The Interactive Evolution of Technical Mediation and Human Presence

The development of Future Communities is fundamentally rooted in the continuous interaction and synergistic evolution between technical mediation and human presence. Genuine human needs guide technological iteration, while user experience feedback continually drives technological optimization and upgrading.

Through mutual adaptation, a balance of construction elements and optimization of the community system is achieved. From a technology-to-humanities perspective, background relations and alterity relations profoundly shape community needs, structures, and users’ perceptual mechanisms. Therefore, innovation in technical mediation must be grounded in the deep-seated demands of human presence. Conversely, from the driving mechanism of the humanities-to-technology shift, residents’ needs and perceptions also react to the community’s background and alterity relations. At the same time, the concrete experiences of human presence provide a precise basis and a feedback loop for technological refinement. The key to achieving this dynamic adaptation in the construction and development of Future Communities lies in pursuing a highly adaptive and resilient balance (Figure 7).

In the evolution of Future Communities, the roles of technology and humanity exhibit an interactive relationship. Their weighting is not fixed but fluctuates based on different developmental stages and specific application scenarios, achieving dynamic equilibrium. Taking the “Yuhang Xiangwang Community” in Hangzhou as a case study within Zhejiang Province’s 2025 province-wide Future Community pilot initiative:

During the planning and design phase, primary guidance should come from needs identification corresponding to hermeneutic relations and perceptual experiences tied to embodied relations. Through methods such as resident participation and needs assessment, as well as the exploration of multi-layered functional requirements, experiential expectations, and cultural-spiritual aspirations of residents within the Nine Major Scenes of the Future Community, a comprehensive understanding can be achieved. This clarifies the design essentials of perceptual experience and the value foundation of response mechanisms. The Xiangwang Community in Yuhang, Hangzhou, is in the planning stage. The guiding principle was to interpret and embody relationships, laying the foundation for values. Through the establishment of a “diverse consultation mechanism”, they actively identified and interpreted the deep and diverse needs of different resident groups (such as foreign nationals and young entrepreneurs). This is not only about functional needs but also about cultural and spiritual yearnings, such as social interaction and cultural identity. The planning process also emphasized resident participation, allowing residents to fully express their perceptions and experiences of their future living scenarios, thereby clarifying the key design points of perception and experience and the value basis of the response mechanism, and pointing out the “people-oriented” development direction for subsequent construction.

In the development and construction Phase, the focus shifts to the built environment at the level of background relations and digital infrastructure at the level of alterity relations. It is essential to ensure the reliable implementation of community construction and technical systems in terms of safety, completeness, and quality, thereby solidifying the dual foundation of the community’s physical and digital realms. At this stage, the focus of Yuhang Wangdao Community has shifted to the built environment at the “background relationship” level and the digital infrastructure at the “other relationship” level. The community has transformed the identified needs during the planning stage into reliable, safe, and high-quality physical environments. For instance, the “first-of-its-kind town-level immigration service station” was built to meet the needs of foreigners. At the same time, the community has introduced digital technology facilities such as “intelligent interactive machines”. These technologies, as independent and active “others”, actively provide information services and convenient interactions for residents, strengthening the community’s digital capabilities.

During the operation phase, the community enters an iterative cycle centered on evaluation and feedback. The focus shifts to examining the effectiveness of need-response mechanisms within hermeneutic relations and the quality of perceptual experiences in embodied relations across various community scenes. Relying on resident feedback, technological systems and policy processes are continuously optimized, forming a sustainable improvement loop. After the community construction in Yuhang District, Hangzhou enters an iterative cycle of “evaluation-feedback-optimization”, allowing residents to participate in community management directly. Their feedback serves as firsthand evidence for testing the effectiveness of the “demand-response mechanism”. The community continuously evaluates these interpretations from residents to optimize the technical system and policy procedures. Residents also deeply participate in community activities and management by serving as “leaders” and have gained a strong sense of participation and belonging. This personal, high-quality experience is precisely the core pursued by “embodied relationships”.

This context-aware and dynamically adaptive resilient mechanism enables Future Communities to establish a continuously adjusting equilibrium between humanistic demands and technological change, ultimately guiding the community toward truly sustainable and humanized development.

5. Discussion

This study employs quantitative analysis to illuminate the evolutionary trajectory of China’s Future Community policy from its initial “technology-driven” approach toward a “human-centric deepening” paradigm. By integrating Christopher Alexander’s humanistic philosophy with Don Ihde’s theory of technological mediation, we propose a “technology mediation-human presence” development pathway.

(1)

Theoretical Construction and Practical Pathways

Using an LDA topic model, this study validates the intrinsic unity of technological and humanistic semantics within the policy. The analysis reveals that six major policy topics encompass dual dimensions, with the role of technology gradually shifting from a dominant “other” to an embedded “mediator.” This finding resonates deeply with Alexander’s concept of the “Quality Without a Name” and Ihde’s theory of fourfold relations. The “Nine Major Scenes” of the Future Community serve as concrete carriers of this concept, while a four-dimensional framework—comprising the built environment, digital technology, demand responsiveness, and perceptual experience—provides the implementation pathway. The key to practice lies in constructing a closed-loop of “demand feedback-system optimization”: precisely capturing needs through co-creation during the planning phase, ensuring the open compatibility of digital facilities during the construction phase, and leveraging tools like digital twins for continuous iteration during the operation phase, thereby enabling technology to function as a mediator serving humanistic values truly.

(2)

International Reference and Local Innovation

The evolution of China’s Future Community offers a unique case study for global smart city development. Its early technology-led phase aligns with the international “technology-push” paradigm, while its subsequent human-centric shift synchronizes with the global trend toward “human-centered smart cities.” Compared to specialized models like Japan’s “Saino Sato” in elderly care or the walkability strategies of Arlington, USA, China’s Future Community achieves a more systematic integration of values through its “Nine Major Scenes.” This holistic intervention at the community scale provides a transferable policy practice for balancing technological empowerment and humanistic values across diverse contexts.

6. Conclusions

This study conducted a semantic analysis of 40 domestic policy texts from 2014 to 2024 based on the LDA topic model. The findings reveal that policy themes can be categorized into technical and humanistic dimensions, with community policy discourse exhibiting a three-phase evolutionary characteristic: “technology-dominant—value turn—human-centric emergence.” The semantic weight of policies has gradually shifted from technical indicators toward humanistic demands, while technological systems have transitioned from instrumental and dominant roles to supportive and mediatory carriers. Accordingly, this study proposes a Future Community development pathway centered on the interaction between “technical mediation” and “human presence”, providing both theoretical depth and practical innovation for community policy formulation and spatial design.

Future research should further explore how to achieve a dynamic balance between technical mediation and human presence within complex contexts involving multiple stakeholders. Particular vigilance is required to prevent high-tech means such as intelligence and digitalization from being reduced from tools to end goals—overshadowing the social attributes and humanistic essence of communities and deviating from the original purpose of community design and the central role of human subjectivity. On the other hand, human-oriented expressions in current policies, such as All-age Friendliness, Co-construction and Sharing, and Participatory Governance, still largely remain at the vision level and lack operable, quantifiable evaluation indicator systems. Follow-up studies should focus on constructing a scientific and systematic quantitative evaluation framework for human-centered spaces, and embed such standards deeply into the full lifecycle—from community needs assessment and planning, through design, to construction implementation and operational management—to promote the continuous optimization and contextual adaptation of humanistic evaluation systems in practice. This will be a critical issue for the high-quality development of future communities in China. Finally, “This article focuses on establishing a collaborative framework for technology and human factors in the development of future communities, aiming to provide a cross-scenario applicable logic. Of course, the development of communities is inevitably embedded in complex ‘built environment’ and policy contexts. These factors, as key application scenario variables, how they will interact and adapt specifically with the ‘technology–human’ collaborative model proposed in this article, are a highly valuable research direction and will also be the focus of our future empirical research for deepening.”