Bibliographic record
Abstract
Arresting Cinema provides a long overdue theoretical intervention in Surveillance Studies by 'provincializing' the existing Western bias in studies of surveillance cinema, a bias that 'resembles the landscape of Surveillance Studies-and surveillance geopolitics-itself' (pg. 7). As Fang astutely notes in her accessibly written book, scholarly studies of surveillance cinema, including monographs by By contrast, Arresting Cinema argues for the exploration of surveillance films, cultures, practices and customs in post-colonial and non-Western spaces outside the Global North, such as Hong Kong. Because Hong Kong is uniquely positioned as a significant film production centre in relation to the United States and mainland China, its surveillance films serve as alternatives to both Western-centred and Chinese discourses on the practice and value of surveillance in society. Here, Fang uses Hong Kong surveillance cinema as part of a larger theoretical and methodological argument for urging surveillance scholars to consider films outside of the existing Western 'canon' of predominantly English-language surveillance films centred on white bodies. 1 Yet she also considers Hong Kong cinema as a regional film culture with its own local film traditions. Treating surveillance as an enduring motif that has been tied to prevailing local, cultural concerns, Fang examines the multiple genres that make up Hong Kong surveillance cinema beyond the genres (e.g., dystopian speculative fiction) most typically associated with surveillance. In addition to espionage and crime films, surveillance themes also surface in a diverse range of unconventional genres, such as comedies, romances, gambling films, and tenement films.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".