Bibliographic record
Abstract
This poetic expression piece details the experiences of a migrant woman arriving in a new host country. While the piece it is not based on the lived experience of one specific migrant woman, the voice of one woman is used to represent a collective voice. This collective voice is comprised from all the Ukrainian migrant women participants that took part and shared their experiences in our research studies within a wider program of research on migrant women who settle in Canada. This poetic expression piece explicates the challenges and worries that this hypothetical migrant woman undergoes with seeking employment, finding affordable housing and food, the constant worries around health and wellbeing, and the guilt of having relocated to a new country. The intention of this poetic expressive piece is to help readers connect, on an emotive level, with the lived experiences of a vulnerable population. The world is currently experiencing the largest displacement of people since the second World War. Providing a means to share stories of experience can lead to a collective understanding of experiences and generation of solutions to support such populations.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.027 | 0.015 |
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".