The Rise of Populist Conservatism and Public Service Management
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.
Bibliographic record
Abstract
The rise of conservative populism in the United States is evident with the election of Donald Trump whose campaign focused on a fear of otherness, a resentment of elites (including bureaucrats), and an emphasis on self-interest. This paper will focus on populist policies and actions introduced during Stephen Harper’s tenure in government. Many of these policies were directed specifically towards the public service including the reduction of public servants, unilateral changes to labour laws, and the politicization of the public service through a proposed niqab ban. While the influence of populist conservative policies has caused noticeable resentments between public servants and the Conservative Party, public servants should reconsider their position within democracy as not focused on their compatibility with the government of the day, but rather with their adherence to the values of inclusion, fairness, and neutrality. While the public service must constantly adapt to the will of the political branch of government including more populist governments, these core values should be celebrated through active implementation and leadership to aid in the development of a positive relationship with both the political arm of government and the public more broadly. These values provide a means for individual public servants to invest their motivation into values that they can treat as fundamental to their role in democracy.
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 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 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it