Observing political and societal changes in Finnish parliamentary speech data, 1980–2010, with topic modelling
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
Parliamentary speech reflects many events, changes and developments in society, as well as shaping them by influencing legislation and public interest. Knowing what topics have been dominant in parliamentary discussions can reveal what has been considered important at the time the speech was given. This knowledge can be achieved computationally with topic modelling, which can identify latent topics in large numbers of texts. Currently, the method is still underused in parliamentary studies and has only previously been used once with Finnish parliamentary speeches. This article aims to create and validate a topic model offering a robust overview of Finnish parliamentary speeches from 1980 to 2010, and to demonstrate the validity of the model by examining peaks in topic occurrences and comparing them to the historical and societal context at the times. The topics ‘energy’, ‘employment’ and ‘democracy’ were selected for closer inspection.
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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 | 0.000 |
| 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