Normalisation of evacuation under slow emergencies: The imposed story of ‘Beautiful New Hong Kong’
Bibliographic record
Abstract
Abstract Hong Kong, in contrast to its previous image as a glamourous global city, has recently been associated with negative keywords such as oppression, fear, violence and even human rights emergency, following the 2019 Anti‐Extradition Law Movement and later the implementation of National Security Law (NSL) in 2020. Meanwhile, the Hong Kong Special Area Administration presented a post‐NSL policy direction as promising a ‘Beautiful New Hong Kong’. This paper is aimed at understanding how Hongkongers have continuously lived with/against the imposed (re)writing of Hong Kong. We examined how Hongkongers have been taking initiatives to raise awareness about the ‘slow emergencies’ in Hong Kong and to counter it in various forms of ‘evacuation’, whether they are on the move or staying put in place, in order to pursue future‐making. We carried out a multi‐sited study on the two kinds of Hongkongers between January 2020 and August 2023. We talked to those who already left Hong Kong for Taiwan, the UK, Canada, and so forth, and with those who were debating about relocation and at the same time preparing for departure if necessary. We strategically read ‘evacuation’ in two senses: First, evacuation responds to emergencies and therefore by adopting ‘evacuation’ is itself a disagreement with the Beautiful New Hong Kong policy as curated by the state. Second, evacuation responds to geography of future and politics of simultaneity. We conceptualised ‘normalisation of evacuation’ to understand the future‐making behind the move in Hong Kong. The particular kind of evacuation discussed took shape in two forms, relocation elsewhere and reorganisation in situ, both of which, in our analysis, are demonstrating Hongkongers' agency in pursuing geographies of future beyond the state‐led agenda.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".