Some thoughts on Experimentation as a Way to Implement Translation: From the second workshop: “Interdisciplinary reading, measurement and notation of ambiances”, Montréal 2015
Bibliographic record
Abstract
Presentation of the GDRI :This CNRS International Research Group (GDRI) was initiated by the International Ambiances Network to explore the issue of ambiances in translation. The word ‘translation’ should be taken in the broad sense of the term, and not reduced to a strictly language-based meaning, though this aspect is obviously present in the project, indeed a key component. By putting the accent on translation, our purpose is to acknowledge the plurality of versions of and means of access to ambiances, to bring into play the notion of ambiance by situating it in a collaborative process; and to address the topic of architectural and urban ambiances by looking at the disparities and shifts this topic involves.Furthermore, by investigating ambiances in terms of translation, we draw together several strands:- We stand at the meeting point of science, enterprise and art. The translations carried out as part of the project will draw on learning, methods and resources from these three worlds.- Overall we propose to adopt a pragmatic posture. We intend to use experimentation in our work on ambiance, focusing on the effects produced, the consequences and movements of this notion.- The translation problématique serves as both a point of entry to the topic of ambiances and as a collaborative working principle for our inquiry. With regard to methodology our approach will involve ‘putting ourselves in translation’.This communication took place in the 3rd Seminar "Epistemological translations", in the Session "Works in progress": Following the Montreal Workshop: A view from Hexagram - Which lessons to highlight? - Experimenting a partition.
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 | 0.049 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.033 |
| Scholarly communication | 0.022 | 0.014 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".