Multimodality and socio-materiality of lectures in global universities’ media: accounting for bodies and things
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lecture prevails as a ubiquitous teaching and learning method across universities worldwide. Whereas lectures have been conceptualized from various text and language-centred perspectives, lecture’s materiality has been scarcely explored, despite the development of “beyond-the-verbal” approaches to communication, practices and learning. To address the gap, this article explores socio-materiality of communication in 10 live recorded lectures, which also had the greatest number of viewers, on the websites or YouTube media channels by “top-ranked” universities in India, Japan, Russia, Egypt, Palestine, Spain, the USA, the UK, Italy and Canada. To do so, a pragmatic semiotic analysis of non-verbal elements of lecture is applied on the videos to “map” its material ingredients and explore related social meanings. The findings point at a few salient things and body characteristics in the sampled lectures, such as the monofocal lecture platform, the omnipresent blackboard, underrepresentation of female lecturers, low diversity and use of technology. We unpack these via “body and thing idiom” and suggest that the lecture needs to be conceptualized as a multimodal, socio-material performance. The article calls for wider acknowledgement and integration of materiality, embodiment, and multimodality in university lectures and the work done to understand and develop teaching at universities.
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.
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 | 0.000 | 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 it