What Was Said? A Discourse Analysis of a Famous Finnish Radio Journalist’s Virtuous Monologues
Bibliographic record
Abstract
The aim of this article is to study a well-known radio journalist and media-educator Hannu Taanila’s radio programs in a state-owned Finnish Broadcasting Company. Hannu Taanila is an influential media person whose radio programs were famous and popular. This article concentrates on Hannu Taanila’s radio monologues. The research data includes 16 radio programs broadcast in 2005. Each program lasted for 45 minutes and all of them were recorded, transcribed, and analysed by discourse analysis. This article focuses on describing and discussing this famous radio speaker’s image, his language and editorial practice: What kinds of interpretative discourses did Hannu Taanila construct in his radio speeches and which were his positions of media education in his radio program? The results of this research show, that the radio as a public media still has the possibility to fulfil the basic educational purposes of national broadcasting.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".