Vote Compass 2023
Bibliographic record
Abstract
This dataset was produced from the online public engagement tool Vote Compass used in general elections in New Zealand and attracted over 300,000 respondents in each election it was run. Vote Compass is an interactive electoral literacy application that approximates a user’s policy alignment with the various parties contesting a given election race. Survey items in Vote Compass are designed to reflect propositions that are salient in the public discourse at the time of the election. The data provides detailed insight into voters’ views which could be related to party policies and campaign events in an election. It was produced in collaboration between Canadian academics from Vox Pop Labs, New Zealand academics including Jennifer Lees-Marshment, and media organisation TVNZ. Data was available to collaborators during 2023; it was not made publicly available due to rules in New Zealand at the time.
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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.009 | 0.011 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.204 |
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".