Bibliographic record
Abstract
Abstract In my thesis work, using expressive gestures, feminist theory and embroidery, I have explored experiences of immigrant women and their continuous struggle to thrive in a new homeland. My work is informed by my experiences as a first generation immigrant woman from Sri Lanka as well as my awareness and experiences of other immigrant women’s experiences from other countries. Although some women have lesser challenges, most immigrant women struggle to thrive in unfamiliar surroundings. This struggle has been a recurring theme in immigrant women’s lives throughout history, and women continue to go through immense hardships in trying to merge into a new society. While still daydreaming of their motherlands, most immigrant women suffer emotionally and psychologically due to lack of extended family support, education, finances, language skills, social and work skills, as well as tensions between traditional and cultural expectations. In spite of these obstacles immigrant women continuously make an effort to reclaim their strength and power. With advances in education and life experiences some of these difficult issues are fading away in my life, although, sometimes they do haunt me. In my artwork I have explored these common experiences and challenges overcome by me as well as other immigrant women through feminist theory, drawing and sculptural techniques and used embroidery, sewing and stitching to bring them to life. I hope to generate awareness through my artwork of women’s experiences that will influence the changes that contribute the empowerment of women.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.013 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".