Must We Talk about Populism? Interrogating Populism’s Conceptual Utility in a Context of Crisis
Bibliographic record
Abstract
Abstract John Gerring identifies eight criteria to help assess the utility of a concept: familiarity, resonance, parsimony, coherence, differentiation, depth, theoretical utility, and field utility. Populism has often been challenged on these despite much work done by scholars to help clarify and sharpen the concept. Nevertheless, three central criticisms persist: the term remains conceptually loose; analysis is often underpinned by an unacknowledged normative bias toward liberal democracy; and, the concept often acts as a label used to sideline challengers to the political status quo, despite crucial differences between these on socio-economic, political, and identity inequalities. Its conceptual utility is therefore questionable as so-called populism displaces the inequalities; particularly, political inequality, which originally engendered the phenomena in the first place. The article concludes by recommending a return to more traditional concepts such as the left/right axis to help redirect debate to more promising lines of inquiry, which can help resolve what I call the “crisis of inequalities.”
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 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 | 0.028 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.019 | 0.119 |
| Scholarly communication | 0.021 | 0.024 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".