A Ugandan Poet Remembers the Rwanda Genocide on Facebook in Canada: The Transnational Aesthetics of Juliane Okot Bitek’s 100 Days (2016)
Bibliographic record
Abstract
In 2014, Juliane Okot Bitek decided to commemorate twenty years of the Rwanda Genocide by writing a poem a day for 100 days on her Facebook page. This sequence of poems was later published in 2016 by the Alberta University Press as 100 Days which won the 2017 Glenna Luschei Prize for African Poetry and was nominated for three other prizes – the 2017 Pat Lowther Award, the 2017 Dorothy Livesay Award for Poetry, and the 2016 Foreword INDIES Award for Poetry. This paper explores four issues: the significance of Facebook and other social media as the space where the poems were first published; the major issues that Bitek raises in this collection; the manner in which she raises them; and finally, but not the least, the transnational aspects of the collection.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.044 | 0.019 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".