Bibliographic record
Abstract
The purpose of this article is to understand how a corporate museum in Kuala Lumpur, Malaysia works to create proleptic myths of nationhood to under-gird a broader state-centric project of nationalist—capitalist modernization. The article examines how these myths are expressed in the museum's design plans and are manifested in the museum's displays and spatial layout. From this analysis it becomes apparent that, first, the museum's designers intend for Malaysian museum-goers to both learn and embody particular myths of national modernization. Second, the museum's displays are dedicated to establishing a Malay-centric origin narrative for the contemporary nation-state. Third, as one moves through the museum, Malay-centrism gives way to narratives of a `multi-racial' society that link technological modernization with social progress. Eventually, however, `race' is trumped by `class' as the social identity category deemed appropriate for `information age' citizenship and nationhood in Malaysia in a story that parallels broader cultural and political—economic state-centric aspirations to achieve `development'. The deployment of `class' in this context melds strategies of government with selective aspects of neoliberalism that seek to manage the possible cultural and political experiences of nationalist—capitalist accumulation and democratic authoritarianism in contemporary Malaysia. I suggest that while these aspirations expressed through the design of the museum might appear to overcome certain limitations of racial communalisms among different Malaysians, they also dissemble underlying symbolic and material violence that enforces a state-centric stability on the possible meanings of citizenship and national identity in contemporary Malaysia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.027 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".