Urban rejuvenation through collective (en bloc) sales in Singapore: Property rights or property wrongs?
Bibliographic record
Abstract
In land-scarce Singapore, which covers only 693 km2, the government is constantly grappling with the issue of judicious allocation of resources between competing uses. In order to generate more housing stock for an increasing population, which is expected to hit 6.5 million by 2027, the government actively promotes private-sector-led redevelopment and urban rejuvenation. One of the measures taken to facilitate such redevelopment involved the enactment of radical legislation concerning collective sales. In a collective sale, all owners of separate units within a development agree to sell their properties collectively and at the same time to a single buyer. Such a sale is feasible when the site has redevelopment potential. In the past, when a collective sale of a development was proposed in Singapore, there had to be unanimous consent among the property owners. Arising from legislative amendments in 1999, however, where just a majority of owners in a development agreed to sell their units, the unwilling minority would be required to sell theirs too. Not unexpectedly, this law was perceived as an abrogation of fundamental property rights in Singapore. It evoked much discontent, resulting in numerous cases being brought before the Strata Titles Board and courts. Myriad objections were raised by the minority, and several cases which came before the Strata Titles Board and the Singapore Courts are singled out in this paper for further discussion. They showcase the legal complexities that surround the central issue of how and to what extent the minority’s property rights can (or should) be safeguarded in the face of majority rule in collective sales. While the Canadian provinces of New Brunswick, Nova Scotia and Ontario had already implemented 80 per cent majority rule for collective sales in 1969 and 1989, respectively, this paper provides an Asian perspective by focusing on the Singapore position and making reference to the position in Hong Kong, which not only faces similar land scarcity and urban renewal issues, but also has similar legislation. It cannot be gainsaid that one of the positive effects of the collective sale phenomenon in Singapore has been land maximisation and urban rejuvenation, but in the aftermath of this phenomenon, this paper posits that the sacrifice by the minority of their property rights has resulted in property wrongs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| 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".