Bibliographic record
Abstract
IntroductoryThis paper discusses how the learning of English in Japan,or maybe the English learned by students in Japan, has appeared to the writer in the last quarter of a century.It will be suggested that not much has changed during this time and a number of reasons why this may be so will be suggested.I base the discussion on observations and experiences related to English use by students of English in Japan, and try to draw out from these what can be surmised about the reasons for the situations described.The selection of the situations and other matters taken up is idiosyncratic and entirely the responsibility of the writer,but they are occurrences that have been experienced by the writer.The opinions developed from these situations have been reached through much reading and thinking about the background to what happened (as reported here) however, and they relate especially to situations where there are communication breakdowns and other dissonance in the language classrooms and other language controlled environments I am acquainted with.I have been teaching at an established college for most of the period covered,and much of my experience and the opinions I have formed are colored by experiences in formal settings where the students are recent high school graduates.I have however also taught classes for the general population during these years and have had the opportunity to talk to many long time learners of, mainly, English.In my professional activities (as a member of JALT［Japan Association for Language Teaching］ )I have taken part in a so called " Peer Support Group"that helps budding writers to write up their language research by helping to get the papers (drafts?)they generate under control and into a publishable format.The papers we work with in the peer group are often very raw,before convention has been imposed and softening of edges has taken place.Papers by non-native English speakers initially display many of the shortcomings I discuss below.I have also published on less general aspects of teaching and language learning environments,the classroom environment,large classes,and computer assisted learning, among other topics.Having given oral presentations in these areas, I have had occasion to reflect my opinions in the feedback I have been subjected to through these activities.My inability to distinguish much change over the years can be put down to a number of reasons.One would be that having become inured to what is going on around me I have ⎜ ⎜ 15
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".