Bibliographic record
Abstract
Singapore’s 2020 general election was held amidst the most serious public health and economic crises in the country’s history. Despite expectations that these parallel crises would precipitate a flight to safety and result in a strong performance by the dominant People’s Action Party (PAP), the ruling party received its third-lowest popular vote share (61.2 percent) and lowest-ever seat share (89.2 percent) since independence. This article engages explanations for the unexpected results and argues that the vote swing against the PAP was enabled by a hitherto largely overlooked factor: the 2020 election included two opposition parties that could credibly compete with the PAP on the valence considerations that drive voting behaviour in Singapore, giving voters a perceived safe alternative to the PAP at the constituency level. Quantitative tests support the notion that party credibility—rather than demographic factors, incumbency advantages, Group Representation Constituencies, or assessments of the PAP’s fourthgeneration leaders—best explains variation in the vote swing against the PAP. Ultimately, the results suggest that the PAP’s monopoly on party credibility is no longer assured, thus portending greater opposition competitiveness and pressure against the PAP in future elections. Nonetheless, the PAP’s dominance remains intact and there is little evidence of a general appetite among the electorate for a non-PAP government, suggesting the likelihood of smaller course corrections rather than major steps towards democratization in the coming years.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
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".