Translation and its discontents: key concepts in English and German history education
Bibliographic record
Abstract
Key terms and concepts are crucial tools in teaching and learning in the disciplines. Different linguistic traditions approach such tools in diverse ways. This paper offers an initial contribution by a monolingual Anglophone history educator in dialogue with German history educators. It presents three different scenarios for the potential of translation between German and Anglophone research communities. In the case of Geschichtsbewußtsein or ‘historical consciousness’, the Anglophone field has already been enriched by the introduction of a new concept over the past decade. In the case of the fundamental group of concepts – ‘source’, ‘evidence’, ‘trace’ and ‘account’ – the Anglophone field is shown to be in surprising disarray, but clarification is within reach. German history education researchers may have a similar need; if so, perhaps they can benefit from the English language discussion. In the third case, that of Triftigkeit or ‘plausibility’, the German field is poised, again to make a significant contribution to a gaping hole in the theory, research and practice of Anglophone history education.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".