Bibliographic record
Abstract
It was in the 1970s that the object of study in literature departments began to change, under the impetus of novel approaches, some radically new and others renewed forms of older ones—structuralism, semiotics, intertextuality, psychoanalysis, pragmatics, deconstruction, reader-response theory, hermeneutics, discourse analysis, etc. Many (but not all) of these were French in origin, at least in part: the names of Lévi-Strauss, Barthes, Kristeva, Lacan, Derrida, Ricoeur, Foucault can be cited. And along with the change in the definition of the object of study came a change in the way literature departments defined themselves and their role. This is clear from the way department of literatures renamed themselves and introduced new programs. These changes came about at different times in different places, dependent in good part on the amount of access that existed to the publications—many of which were in French—but especially to the debates they gave rise to. It was in this context of expansion and of redefinition—presented here in terms of my own particular history—that an interest in translation, and later in Translation Studies, developed. Of course, translation was not an entirely new object of study; linguists and students of literature (especially of comparative literature) had on occasion acknowledged its existence, and even at times, its importance. However, it was only with the advent of the new approaches to texts, to reading, to interpretation, and to the context of the transmission of meaning(s) and of expression, that a conception of the importance of translation, and of its interest from a theoretical point of view, was able to develop. This led, in the 1980s, to the construction of a new discipline—Translation Studies.
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 | 0.038 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.011 | 0.042 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".