Bibliographic record
Abstract
My family and I immigrated to Canada over 25 years ago, searching together for a better life. Though we came with hopes for new and better opportunities, our successes came with a price-years of struggle and isolation. We landed on the prairies and were confronted with a society very different than the one we had left. My parents laboured to raise seven children, each grappling with explicit daily outbursts ofracism and violence, language acquisition, and the effort to find a place in a new culture. I grew up treated as an alien-an Asian female who doesn't quite belong here and the people who surrounded me made certain I knew it. Through the years I have fought to understand my heritage and the inherent contradictions in my attempts to bridge the western and eastern cultures. Although the East and West embody vastly different philosophies, I came to recognize that my role as female remains the same. I began to understand that not only do I have to deal with the fact that, no matter how long I have lived here, no matter what I do, I remain an alien in this country, and awoman at that. I share this disadvantage with women across the world. My introduction to feminism provided me with a comprehen-sive analysis that enabled me to grapple with these issues, explicitly identifying racism, gender inequality, and the expression of power relations. Frontline experience became more It has become common to hear age-old statements like should go back where they came from, and should come here on legal terms and not be allowed to jump queue:'
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.014 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.045 | 0.011 |
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".