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Record W4386195873 · doi:10.1038/s41597-023-02464-w

Digitization of the Australian Parliamentary Debates, 1998–2022

2023· article· en· W4386195873 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueScientific Data · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsParliamentDigitizationDemocracyPoliticsResource (disambiguation)MetadataPublic administrationPolitical scienceLibrary scienceData scienceSociologyComputer scienceWorld Wide WebLaw

Abstract

fetched live from OpenAlex

Public knowledge of what is said in parliament is a tenet of democracy, and a critical resource for political science research. In Australia, following the British tradition, the written record of what is said in parliament is known as Hansard. While the Australian Hansard has always been publicly available, it has been difficult to use for the purpose of large-scale macro- and micro-level text analysis because it has only been available as PDFs or XMLs. Following the lead of the Linked Parliamentary Data project which achieved this for Canada, we provide a new, comprehensive, high-quality, rectangular database that captures proceedings of the Australian parliamentary debates from 1998 to 2022. The database is publicly available and can be linked to other datasets such as election results. The creation and accessibility of this database enables the exploration of new questions and serves as a valuable resource for both researchers and policymakers.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.130
GPT teacher head0.397
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it