Bibliographic record
Abstract
In Memoriam Professor Geoffrey V. Davis Pamela McCallum Readers of ARIEL will be saddened to learn of the death of Professor Geoffrey V. Davis, a scholar who throughout his career was a strong advocate for Commonwealth and subsequently postcolonial literatures. Geoff taught at Aachen University (Germany) and had research and teaching fellowships at the Universities of Innsbruck (Austria); Verona (Italy); Cambridge (UK); Curtin (Australia); Växjö (Sweden); and Texas, Austin (USA). The author, editor, or co-editor of more than thirty books, Geoff engaged with a wide range of issues in postcolonial studies. His first commitment, and one that continued throughout his life, was to Zimbabwean and South African literatures. Matatu: A Journal for African Culture and Society, of which he was a founding co-editor, continues publication to this day. Recently, together with Ganesh Devy and Kalyan Chakravarty, he co-edited four volumes that situated indigenous issues transnationally: Indigeneity (Orient Blackswan, 2009), Voice and Memory (Orient Blackswan, 2011), Narrating Nomadism (Routledge India, 2013), and Knowing Differently (Routledge India, 2013). The [End Page 1] series Cross/Cultures: Readings in the Post/Colonial Literatures and Cultures in English, which he co-edited with Gordon Collier, has proven to be an indispensible resource for scholars in postcolonial studies. One of Geoff’s books, Voices of Justice and Reason (Rodopi, 2003), took its title and epigraph from a comment by Nelson Mandela that the arts were sites where the case for resistance, liberty, beauty, and equality might still be made even in the darkest years of Apartheid. That claim echoes powerfully in Geoff’s research and writings and in the many conferences, seminars and talks he participated in or organized. He served as Chair of the European Association for Commonwealth Literature and Language Studies (EACLALS) for three terms (2002–2005–2005–2008–2011–2014), and he was international Chair of ACLALS from 2008–2011. My personal memory of Geoff is his participation in a small session at the ACLALS conference in Vancouver in August 2007. He was a welcoming, insightful and gracious presence in the discussion. His voice will be profoundly missed. [End Page 2] Pamela McCallum Editor, ARIEL 2001–2011 Copyright © 2019 Johns Hopkins University Press and the University of Calgary
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.069 | 0.059 |
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".