Some Problems in Recording and Analyzing South African English Vocabulary (The Experiences of an Outsider)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article describes some problems in collecting and studying South African English vocabulary on the basis of non-South-African texts faced by a linguist who is a native speaker of American English. The questions are thus: Are non-South-African texts just as reliable as South African texts? More reliable? Less reliable? And is a linguist who is a native speaker of a different variety of English just as reliable as a native? More reliable? Less reliable? It is suggested here that the best way of studying a language, if possible, is by having both insiders and outsiders look at the material. <b>Keywords:</b> abbreviations, african languages, afrikaans, american english, australian english, black english, british english, canadian english, capitalization, careful use of primary and secondary sources, convergence, definitions, dictionaries, differential dictionaries, dutch, english, etymology, family names, folk etymology, french, german, hebrew, initialisms, latin, lexicography, misprints, nonce forms, overdefinition, personal names, place names, postal terms, prepositions, productivization, reflexive pronouns, slang, slips of the tongue, south african english, spelling, status and usage labels, surfers' terms, teamwork, underdefinition, yiddish, zoological terms
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it