Bibliographic record
Abstract
'Hong Kong Story' has always been an euphemism of 'Hong Kong's history' in enunciating the characteristic of local history. In the colonization era, Hong Kong history was indeed a colonial history because started from the very early period, the historical archives were written by either the missionaries or aristocracies, which laden with dominant European discourse. The changes in the political and cultural environment because of the 1997 Handover had invoked a blatant identity searching process among Hong Kong writers. After Hong Kong has entered into the post-transitional period, local writers started to re-investigate the history of Hong Kong. The reappropriation of history is the common theme shared by Shi Shu Ching's Hong Kong Trilogy and Dung Kai Cheung's 'The Rise and Fall of Wing Sing Street' and The Atlas: The Archeology of an Imaginary City. The thesis argues that through constant re-narrating Hong Kong history in writing Hong Kong story, not only points to a recognized need in Hong Kong culture to search for a new identity, a new self-consciousness that can claim a different history than what has been instituted in the past colonial discourse and the appropriation of the PRC national discourse at the turn of 1997, but also gives the writer themselves a chance to construct a differentiated and unique identity; because retrieving history in writing fictions is the indispensable for any conception of self or subjectivity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".