Evidence map›Paper›PMID 41838765›Full record

ArticlePloS one2026

Policy Modeling Consistency index-based study on policy synergy for sustainable artificial intelligence in China's digital cultural industries.

Chen Qu, Xinyang Zhao

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Chen QuShanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China.
Xinyang ZhaoInstitute of Global Urban Civilisation, Southern University of Science and Technology.ORCID https://orcid.org/0000-0001-9037-7626

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper applies the Policy Modeling Consistency (PMC) index model to quantitatively evaluate 32 Chinese policies (2016-2025) promoting artificial intelligence (AI) in digital cultural industries (DCIs). Focusing on policy synergy for sustainable AI, the analysis assesses ten primary variables-including policy objectives, instruments, sustainability integration, and application levels-across national and local initiatives. Results reveal an overall 'Excellent' average PMC score, indicating robust policy design in economic or technological domains. However, some low-grade policies prioritize short-term regulation over sustainable governance. The study recommends embedding 'human-centricity' and 'ethical risk assessment' in sustainability indicators, alongside cultural diversity safeguards (e.g., algorithmic support for intangible heritage). These optimizations can reframe AI as a socio-cultural enabler-not merely a technical tool-advancing equitable, innovative, and ecologically resilient DCIs aligned with Sustainable Development Goals (SDGs).

Indexed as

Artificial IntelligenceCultureIndustryPolicySustainable DevelopmentChinaDigital MediaDigital TechnologyModels, Theoretical

Identifiers

PMID41838765
PMCPMC12991277

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.