Digging into Linked Parliamentary Data (DiLiPaD)- Project Plan
Bibliographic record
Abstract
Parliamentary proceedings reflect our history from centuries ago to the present day. They exist in a common format that has survived the test of time, and reflect any event of significance (through times of war and peace, of economic crisis and prosperity). With carefully curated proceedings becoming available in digital form in many countries, new research opportunities arise to analyse this data, on an unprecedented longitudinal scale, and across different nations, cultures and systems of political representation. \n \nFocusing on the UK, Canada and The Netherlands, this project will deliver a common format for encoding parliamentary proceedings (with an initial focus on 1800 to yesterday); a joint dataset covering all three jurisdictions; a workbench with a range of tools for the comparative, longitudinal study of parliamentary data; and substantive case studies focusing on migration, left/right ideological polarization and parliamentary language. Comparative analysis of this kind, and the tools to support it, will inform a new approach to the history of parliamentary communication and discourse, and address new research questions. \n
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.
How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; both teacher heads agree on what is shown here.
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".