Bibliographic record
Abstract
“Demonstrations” is a collection of six short stories which follow protagonist James Kou, a young, middle-class, Hong Kong Chinese-Canadian immigrant studying English literature in Lennoxville, Québec, and later, returning to his birth place of Hong Kong, as he navigates the multiple facets of his personality and begins to understand who he is and where he comes from. These stories explore issues of internal and external racism, familial relations, the rediscovery of culture, language, ancestry, place, and redemption in the form of restorative relationships. The settings of Lennoxville, a majority white and rural area in Québec, and Hong Kong, a majority Chinese, former British colony, reflect the complications of identity exemplified by James. The historical moment of spring and summer 2019 in which majority of these stories take place, as well, imbues James’s visit with an added significance, as it is in this year China attempts to pass an extradition bill which allows detainment of Hong Kong citizens or citizens from other territories such as Taiwan who are deemed dissidents or criminals. The fear however is that such power would be used to suppress political dissent; the proposed bill as of summer 2019 is another example of China’s encroachment upon Hong Kong, an island which is and is not a part of China. Hong Kong in the summer of 2019 saw some of the largest pro-democracy demonstrations yet.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.350 | 0.119 |
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".