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
ABSTRACT: An analysis of authentic or genuine interactions among Cameroon English speakers reveals that conversational routines in this variety of English differ a good deal from those obtained in other varieties of English, non‐native varieties of English inclusive, and more specifically in native varieties of English. This paper looks at ‘thanking responders’ in Cameroon English speech. The examination of real conversational exchanges between many Cameroon English (CamE) speakers and myself between October 2002 and July 2003 demonstrates that speakers of English in Cameroon use a wide array of expressions to acknowledge thanking, ranging from no acknowledgements at all, namely absolute silence, to such expressions as thank you, thank you too, for nothing, mm, yes, all right, ok and so on which are not very common or attested in native varieties of English. In other words, these expressions which are widespread in Cameroon are not heard too often in other varieties of English while speakers acknowledge thanking. Pragmatically, it is suggested that these thanking responders in CamE somewhat reflect the cultural values of Cameroonians who, in addition to English, speak other African local languages in which thanking and thanking responders are not necessarily similar to those in English. From a pedagogical viewpoint, the paper proposes that the native English forms of this aspect of daily interaction be taught to CamE speakers in the event of cross‐cultural communication and also strongly advocates that local or Cameroonian forms not be considered substandard but introduced in the school curriculum and accepted as appropriate for the local or regional variety.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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