Bibliographic record
Abstract
Whether by speaking or by writing, efforts to communicate can never be completely successful. No two persons can ever have learnt the meaning of any word in precisely the same circumstances. However, where those trying to communicate have undergone similar experiences or where they make much the same assumptions, their chances of communicating adequately will be good. Indeed, members of any close-knit group a family or life-long neighbours, for example need not attempt to be always explicit. Much of what they wish to say to each other is already implied by context of situation, and mere reference to a subject may suffice. In what may be called 'the language of intimacy, a word or two and a glance at a watch could, as we say, 'speak volumes'. Correspondingly, where the backgrounds and assumptions of those attempting to communicate are very different, the difficulties of making each other understand are vastly increased. If they are to communicate at all, they must be explicit. This is most obvious, say, where East tries to meet West, but more insidiously it can occur where both parties are apparently of the same culture and speak versions of the same language.
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.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.078 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".