Languages of Educational Discourse: Process, Procedure and Skill
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
If the way in which educational debate has gone on in England in the last few decades is anything to go by, it is clear that such debate does not take place in a unified discourse in which all participants use the same language, or even the same rules of debate. The very exercise of some people trying to convince others that certain things should happen in education, and that certain other things should not, of course, presupposes that such a common language and such common ground-rules of truth-testing, or at least refutation, do exist and are the stock-in-trade of all who join in the arguments. It only makes sense for one to assert that such and such is the case, or that this ought to happen and that not, on the assumption that others can in some common way test the claims. But this general claim by philosophers and some others about the logical status and presuppositions of argument, while descriptive, is only descriptive in a limited way. That is to say, the claim describes what ought to count as a proper argument; it does not describe how people and agencies of one kind or another actually conduct what they are happy to call 'argument' or 'debate'. Whilst this can be extremely frustrating to the philosophically-minded educator, it has to be accepted that what is factual description for one can seem like simple prescription, which need not be heeded, by another. What is even more galling to those in the community of philosophically-minded educators --I speak at least for myself but I am sure for many more --is that in the world of decision-making the 'proper argument' does not always win the day.
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 | 0.003 |
| 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