Bibliographic record
Abstract
Usually, historians in France recognize that their task is to “make the sources speak”. What might appear to be a simple question of a technical nature (making known what is contained in the sources), however, conceals a balance of power that is certainly inherent to the historical academic field. Indeed, “making the sources speak” poses a problem in terms of both the concept of “sources” and the verb “to speak”. Initially, the crucial issue for a discipline that sees itself as a mode of indirect knowledge was to make the medium transparent, as if we could hear the witnesses directly in order to arrive at the truth of things. Hence the designation of historical material with a set of naturalizing metaphors that have had the crucial consequence of eliminating from historical reflection the meaning effects linked to the conditions of transmission and, in particular, archiving (selection, classification, inventory), which have only appeared on the historians’ horizon since the beginning of the 21st century as part of the “documentary turn”. This has not, however, done away with the question of the voices to be heard in the sources, which has been taken over by ethical concerns, giving to the “archival turn” a distinctly different tone from the “documentary turn”. This raises the question of the extent to which this question of the voices to be recovered not only reintroduces the dream of unmediated access to the past, but also overvalues the individual at the expense of society, as part of a regression in collective rationality.
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 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".