Bibliographic record
Abstract
In 2015, the New Democratic Party won an unprecedented victory in Alberta. Unseating the Progressive Conservatives -- who had won every provincial election since 1971 -- they formed an NDP government for the first time in the history of the province. Orange Chinook is the first scholarly analysis of this election. It examines the legacy of the Progressive Conservative dynasty, the PC and NDP campaigns, polling, and online politics, providing context and setting the stage for the unprecedented NDP victory. It highlights the importance of Alberta's energy sector and how it relates to provincial politics with focus on the oil sands, the carbon tax, and pipelines. Examining the NDP in power, Orange Chinook draws on Indigenous, urban, and rural perspectives to explore the transition process and government finances and politics. It explores the governing style of NDP premier Rachel Notley, paying special attention to her response to the 2016 Fort McMurray wildfire and to the role of women in politics. Orange Chinook brings together Alberta's top political watchers in this fascinating, multifaceted analysis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".