Bibliographic record
Abstract
In 1967, American dialect actor Luis d’Antin van Rooten published his now-classic Mots d’Heures: Gousses, Rames, a non-organic arrangement of French-language words and phrases designed to approximate the speech sounds of Mother Goose Rhymes. Though much read and imitated, these homophonic translations have largely evaded theoretical focus. Perhaps this is because their unique structuring allows them to evade anchorage in any specific contextual frame, and to send up the researcher’s own efforts toward contextualization, which has been prescribed as the methodological “first step” in Translation Studies since the Cultural Turn. Presented here, first of all, is a search for the potential frames of the Mots d’Heures–biographical, inter-textual, cinematic. These homophonic translations, I will then contend with reference to Jean-Jacques Lecercle (1990), exist to defy these frames by collapsing together, at the phono-articulate level, the target text with its most obvious context: the English-language source. Finally, I would contend, this collapse exemplifies the phenomena of “weaning,” “trans-contextual drift,” and “remainder” argued by Derrida (1988) as the enduring property of the signifying structure. The Mots d’Heures serve, then, as a playful reminder, in an intellectual climate where context reigns, of the signifying form’s structural ascendancy over the frame, of its “iterability.”
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".