Bibliographic record
Abstract
Forget left and right. The real divide is technocrats vs. populists. (Freeland, 2010) Technocracy is back (it was never gone) Not so long ago, technocracy was largely forgotten. Then a wave of populism swept across the Western hemisphere. First came the realization that the rise of populist parties and movements in Europe was no longer contained, but a growing political force to be reckoned with. Then came Brexit in the summer of 2016, and roughly half a year later the election of Donald Trump. Since then, politicians and political scientists alike have been scrambling to make sense of the populist challenge to democracy. In the course of these events, technocracy has increasingly been invoked as the principal reason behind the current surge in populism. Taken to its radical conclusion, this link between populism and technocracy means, as summarized by journalist, author and (at the time of writing in 2019) Deputy Prime Minister of Canada Chrystia Freeland in the epigraph to this chapter, that technocracy vs populism is now the defining political conflict of our era. This is of course a rough outline of recent events, but there is certainly a current resurgence of interest in technocracy driven by the widespread search for causes and responses to the success of populist movements and parties in recent years. However, this resurgence also follows decades of relatively sustained silence on the topic of technocracy, roughly since the beginning of the 1980s, meaning that technocracy plays an increasingly vital role in attempts to come to grips with the political challenge of the foreseeable future, while at the same time being rather poorly understood. The purpose of this book is to provide some measure of improvement of this situation and take a step towards a better understanding of technocracy. In other words, the book reverses the current rediscovery of technocracy as an explanation for populism. Rather than arriving at technocracy through the question of populism and its causes, I will arrive at populism as a corollary to the question of technocracy only in the concluding chapters of the book. To be clear: this is not a matter of dislodging technocracy from populism or exonerating it from culpability in current challenges to democracy. On the contrary, I fully agree that technocratic policy and politics is one of the principal reasons for the current resurgence of populism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.061 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".