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Record W4408448769 · doi:10.1080/10670564.2025.2477200

Navigating Through The Fog: Reflexive Accounts on Researching China’s Digital Surveillance, Censorship, and Other Sensitive Topics

2025· article· en· W4408448769 on OpenAlex
Ariane Ollier‐Malaterre, Emilie Szwajnoch, Alexander Trauth-Goik, Ausma Bernot, Fan Liang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Contemporary China · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of OttawaUniversité du Québec à Montréal
FundersEuropean Research CouncilSocial Sciences and Humanities Research Council of CanadaNarodowe Centrum Nauki
KeywordsReflexivityCensorshipChinaMedia studiesPolitical scienceSociologyLawSocial science

Abstract

fetched live from OpenAlex

Researching China’s sensitive topics, such as digital surveillance and censorship, exposes scholars to mounting challenges including difficult field and internet access to quality information, scrutiny and security of research participants and researchers, and positionality amidst geopolitical tensions. This article presents self-reflexive accounts from six scholars of diverse backgrounds, fields, and career stages who work through varied methods, positionalities, and epistemic approaches. We share our research journeys’ challenges and coping strategies to aid scholars, beyond China or digital surveillance and censorship. We propose that reflexivity is essential for scholarly work on contentious or opaque topics; that the China studies research community should organize knowledge sharing and cross-training; and that academia should create emotional support structures for researchers who encounter surveillance and restrictions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.367
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it