Filling the blanks: How Chinese students’ Study Experiences at Queen’s University gave them more Complete Knowledge about their Country and Changed their View on Contemporary China.
Bibliographic record
Abstract
In Canada academic freedom and the right to criticize are often taken for granted. Under some more repressive regimes, however, people grow up in an education system that bans the inquiry in certain areas and imposes an official narrative on the discussion of many topics. As an international student from China (PRC) studying at Queen’s, I have greater access to different perspectives on China and its history than before, and the more complete knowledge I obtained helped me to construct a more informed perception of my country. This inspired me to explore the similar change that happened to other Chinese international students at Queen’s, with a focus on how their views on contemporary China’s social and environmental issues, such as China’s air pollution, migration workers, and left-behind children, might have been influenced by their experiences at Queen’s and the chance they had to relearn their native country. Except its academic value, this project can make a difference to the Queen’s community by raising attention for Chinese students, who count for 59% of international students studying at Queen’s (Queen’s University 2017-18 Enrollment Report) but do not have a voice proportional to the community size. Besides, the interdisciplinary nature (history and human geography) of this project means it can be developed into more in-depth researches in the future, possibly during the coming summer.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".