Bibliographic record
Abstract
Dr Raphael d’Abdon is a writer, scholar, spoken word poet, editor and translator. In 2007 he complied, translated and edited I nostri semi/Peo tsa rona, an anthology of contemporary South African poetry. In 2011 he translated into Italian (with Lorenzo Mari) Bless Me Father, the autobiography of South African poet Mario d’Offizi. In 2013, he compiled and edited the collection Marikana: A Moment in Time. He is the author of three collections of poems, sunnyside nightwalk (Johannesburg: Geko, 2013), salt water (Johannesburg: Poetree Publishing, 2016) and the bitter herb (East London: The Poets Printery, 2018), and he has read his poetry in South Africa, Nigeria, Somaliland, Italy, Sweden and the USA. His poems are published in journals, magazines and anthologies in South Africa, Nigeria, Ghana, Malawi, Singapore, Palestine, India, Italy, Canada, USA and UK, he is South Africa’s representative of AHN (Africa Haiku Network), and he is a member of ZAPP (The South African Poetry Project) and IPP (International Poetry Project), two joint-projects of the University of Cambridge, UNISA and the University of the Witwatersrand, whose chief aims are to promote poetry in schools in South Africa, UK and beyond, and to instill knowledge, understanding and a love of poetry in young learners.This interview is conducted through e mails in the months of April-May 2020 when Corona virus ravished the world. We saw light through the wings of poesy. We reached out each other through questions and answers about poetry, life and the immediate.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.056 | 0.036 |
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".