Podcasts as an emerging register of computer-mediated communication
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
Abstract Podcasts, a relatively recent audio medium, have risen in popularity since their initial appearance in the mid-2000s. Yet, little is known about their lexico-grammatical characteristics and their relation to other computer-mediated and traditional registers. Addressing this gap, we apply Biber-style multidimensional analysis (MDA) to a representative sample of Spotify podcast transcripts and selected computer-mediated registers (e.g., informational blog, interview) as well as traditional spoken registers (e.g., broadcast, conversation). We compare their lexico-grammatical characteristics to those of other registers along the emerging dimensions. We find that, while podcasts share some linguistic characteristics with traditional spoken registers such as broadcast discussion and scripted speech, they are unlike any of the analyzed registers. In fact, their most striking characteristic is their considerable internal variability, likely related to their versatility but also due to their mixing of features and very diverse nature. In short, podcasts are an emerging register of computer-mediated communication.
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 | 0.001 | 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 | 0.001 |
| 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