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Record W2941236730 · doi:10.21315/km2019.37.1.6

The Role of Federalism in Malaysian Low-Cost Housing Provision: The Unexplored Dimension

2019· article· en· W2941236730 on OpenAlexfundno aff
Andrew Ebekozien, Abdul Aziz, Mastura Jaafar

Bibliographic record

VenueKajian Malaysia · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
FundersUniversiti Sains MalaysiaUniversity of Toronto
KeywordsFederalismContext (archaeology)Dimension (graph theory)State (computer science)Government (linguistics)Cooperative federalismGlobeState governmentBusinessPublic economicsPublic administrationLocal governmentPolitical scienceEconomicsGeographyPsychology

Abstract

fetched live from OpenAlex

Various studies have examined federalism in the context of housing provision around the globe.In Malaysia, the tension between the federal and state governments with regard to low-cost housing (LCH) is yet to be explored.This article presents part of the results of a larger research that reveals the tension between federal and state governments with regard to the provision of LCH through a qualitative approach.LCH targets set by the federal government which manifests in five-year economic plans should be met by the various states.To what extent do policy-makers consider the means with which the various states can meet these LCH targets?The states are expected to find the additional funds to deliver the LCH.Findings show there have been instances of a tussle over land and LCH provision between the federal and state governments.Other aspects of federalism which impact on LCH delivery are presented in this paper.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.012
GPT teacher head0.200
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2019
Admission routes1
Has abstractyes

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