Capturing the Realities of Diaspora & Dissident Communities Experiencing Transnational Suppression from the Chinese Party-State Apparatus
Bibliographic record
Abstract
This thesis is an original contribution to academic literature on the lived experiences of diaspora and dissident communities with surviving transnational surveillance from the Chinese party-state apparatus. Written by a community insider, this project brought community knowledge to academia. The author conducted interviews with eleven participants: one identified both as Hongkonger and Chinese, 3 Hongkongers, 1 Chinese, 3 Tibetans, 1 Taiwanese, 1 Uyghur, and 1 white Canadian. The project recorded the experiences and invisible labour of participants, including being defined as “Chinese” in attempted erasure of their ethnic identities, reclaiming their communities and right to self-identity, extensive safety concerns due to fear of being targeted by the Chinese government, and feelings of profound disappointment due to Canadian institutions’ inaction to support and protect them, while staying hopeful for the future. The author also drew boundaries to safeguard certain knowledge from academia, balancing her dual identity as a dissident and researcher.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".