Bibliographic record
Abstract
This issue brings together 10 anthropologists who investigate the potential of multimodality and the role of sensing, as situated social practice, in the complex working of memory. Through video, images, texts and sound—and through collage, installations, embroidery, and drawing—we invite the audience of Multimodality & Society to consider: What are some of the complex relationships between memory and the senses? How does multimodality help us approach the study of remembering and forgetting? This introduction frames our work into current debates in multimodal and sensory anthropology, discusses our approaches to memory, and draws some of the common themes that connect our contributions. Collectively, we investigate memory as sensate, emplaced, and affective, and existing in a complex relation with temporality and practices of forgetting. We are particularly interested in the links between multi-sensory approaches and the possibilities offered by multimodality. We argue that the latter can help us think of sensate memory, and vice versa, studying remembering and forgetting as multisensory can demonstrate some of the potential of multimodal scholarship.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.038 | 0.011 |
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".