Bibliographic record
Abstract
Nigel Lowther Love is associate professor of linguistics at University of Cape Town. He was born in 1950 in the U.K. He received his B.A. (1973), M.A. (1976) and D. Phil. (1976) from Oxford University. His Ph.D. thesis title was: The generative phonological analysis of non-vocalic alternations in Modern French. Nigel Love has been the invited lecturer or conference speaker at universities in: Athens, Birmingham, Bradford, Bristol, Cambridge, Cape Town, Chicago, Copenhagen, Durban, Edinburgh, Grahamstown, Hong Kong, Johannesburg, Jyvaskyla, Kirksville, Montpellier, Mumbai, New Orleans, Nottingham, Odense, Oxford, Paris, Pittsburgh, Quebec, Seville, Stellenbosch, Tambov, Warsaw and Williamsburg. He was the head of Linguistics Department at University of Cape Town (1995-1998). He has been the editorial board member (since 1992) and associate editor (since 2019) of journal of Language and Communication. He was the editor of the journal of Language Sciences (1997-2014). Among his authored and coauthored publications are Generative Phonology: A Case-Study from French (1981), The Foundations of Linguistic Theory: Selected Writings of Roy Harris (1990), Linguistics Inside Out: Roy Harris and His Critics (1997), and Language and History: Integrationist Perspectives (2006). JALDA’s editor-in-chief, Dr. Bahram Behin had the following short communication with Nigel Love.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".