Bibliographic record
Abstract
“It’s a losing battle: my words have no chance against time. Sometimes, unable to catch up with imagination, I leave the battle, candle in hand, in complete darkness.” — from “Trying Again to Stop Time" Jalal Barzanji chronicles the path of exile and estrangement from his beloved native Kurdistan to his chosen home in Canada. His poems speak of the tension that exists between the place of one’s birth and an adoptive land, of that delicate dance that happens in the face of censorship and oppression. In defiance of Saddam Hussein’s call for sycophantic political verse, he turns to the natural world to reference a mournful state of loss, longing, alienation, and melancholy. Barzanji’s poetry is infused with the richness of the Middle East, but underlying it all is a close affinity to Western Modernists. In those moments where language and culture collide and co-operate, Barzanji carves out a strong voice of opposition to political oppression. Readers will return to his work again and again, just as viewers return to a favourite painting. “Like contemporary poets Taslima Nasrin, Adonis, Yehuda Amichai, and Shuntaro Tanikawa, Barzanji’s is a voice in which the native willingly mutates into the global.” — Sabah A. Salih, Translator
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.023 | 0.012 |
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".