A new, comprehensive database of all proceedings of the Australian Parliamentary Debates (1998-2022)
Bibliographic record
Abstract
This database contains data on the proceedings from each sitting day in the Australian Parliament by the House of Representatives from 02 March 1998 to 08 September 2022, in both CSV and parquet forms. These data were parsed entirely from the XML Hansard transcripts available on the Australian Parliament website.<br> The database is organized as follows: <strong>hansard-daily-csv.zip </strong>contains all individual Hansard sitting day files in CSV form. <strong>hansard-daily-parquet.zip</strong> contains all individual Hansard sitting day files in parquet form. <strong>hansard-corpus.zip</strong> contains the full Hansard corpus in CSV form and in parquet form. <strong>hansard-code.zip </strong>contains all the R files we used to build our database, and any necessary CSV files to run those R scripts. The <em>README.md</em> file in this folder contains a detailed description of each script, outlines our workflow, and provides some example R code for users of our database. <strong>hansard-supplementary-data.zip </strong>contains data on Hansard debate topics, and data on divisions in the House that were transcribed during our time frame. This folder also contains the CSV we used to correctly map PartyFacts IDs to the party abbreviations found in our database.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".