The Interface of <em>Nous</em> and Computer in Inter-disciplinary Research, Communication and Education
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 study is a meta-cognitive discussion about whether non-English scientists know about the existence of computer tools – such as monolingual, bilingual and multilingual electronic dictionaries, CAT [Computer Assisted Translation] tools - and whether they know how to use them in order to communicate their inter-disciplinary research internationally. It also discusses what is at stake when concepts such as inter-scientificity (i.e. “bar”, with 17 different terms in Greek) and reverse inter-scientificity (i.e. “πρόγραμμα” [: program] with at least 6 different terms in English) emerge. Then the author of this study claims that only human mind/intelligence (nous) - with the aid artificial intelligence (computer –CAT tools) and through different mental/cognitive processes (noesis) can establish certain criteria in choosing appropriate terms and expressions, so that an inter-disciplinary research can be communicated properly and thus (international) scientific communication can be achieved effectively. Finally, the author of the present study proposes that Higher Education Institutions [HEIs] in North America (the USA and Canada) and Europe should get involved in educating and training both their large number of international students and staff administrative and academic), if a proper international inter-disciplinary communication is to be attained.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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