Rhythms of Silence: Digital audio analysis of Swedish Radio Broadcasting, 1980-1989
Bibliographic record
Abstract
How can silence be studied, and what can we learn from it? This article explores the so-called 'modernization' of Swedish Public Service radio by pertaining to pauses, halts and the absence of content. By applying computational analysis to the broadcasting archive, radio can be explored on a larger scale than previously affordable. The article argues that it is possible to understand the rhythm between more and less dense content by studying the distribution of silence in time. The analysis focuses on how varying degrees of silence are distributed throughout the day in broadcasting by the Public Service Program 1 (P1). Sweden was one of the last western, democratic countries to undergo broadcasting de-monopolization. However, in order to stimulate a modernization process, competition was introduced within the state monopoly before the proper commercialization of radio in 1993. Though the actual effect of this process remains disputed, the last decade of the Swedish radio monopoly is considered a significant media historical period of transition. Whilst the organizational structure endured, public discourse witnessed a clash between new and old ideas concerning the very essence of radio. The period thus enables the study of radio in transition. To grasp the potential effects of these debates and organizational changes on the very content of radio, this study takes its cue from the overlooked but essential matter of silence in the radio medium. Tracing the changes and trends in a set of sample weeks from 1980 to 1989, the results indicate both how the amount of silence diminished and its rhythm became more uniform. Whilst providing insights into the style of Swedish public service radio, the work is also intended to inspire new, creative ways of researching sound media.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".