Relocating Politics at the Gateway: Everyday Life in Singapore's Global Schoolhouse
Bibliographic record
Abstract
Common understandings of international affairs are often expressed through spatial metaphors, such as regional blocs, fortresses, bridges and gateways. These spatial metaphors are widely utilized as they appeal to our common sense. It makes sense to understand and explain world affairs by using expressions and examples that are deeply anchored in our everyday life, in our everyday social imaginaries. Even if we cannot really make sense of what transnational relations look like, we can better understand their use, and function by comparing them, example, to bridges between states.2 The uses and abuses of these spatial metaphors have, however, some limitations as they tend to restrict our capacity to understand the complexity of international affairs. Although the for whom and what purpose question with respect to spatial metaphors has been already explored, spatial metaphors remain of popular use, hence privileging specific interests over others.3 Whereas spatial metaphors tend to reinforce the centrality and the importance of states and actors constructed as relevant to states, such as international organizations and multinational corporations, they also limit our capacity to engage with the diversity and plurality of lived experiences on which these metaphors are based. If a state can define, regulate and institutionalize the ways in which one should bridge to other countries, these official mechanisms usually silence and exclude specific practices serving as bridges between countries as well, even if not officially recognized.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".