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Record W2253813971

Policy Options for the Resolution of Involuntary Resettlements Induced by Hydroelectricity Projects in the Context of Urbanization in China - A Case from Longtan Reservoir

2010· article· en· W2253813971 on OpenAlexaff
Ping Xiao, Qin Chao-jun

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHydropower, Displacement, Environmental Impact
Canadian institutionsMcGill University
Fundersnot available
KeywordsUrbanizationContext (archaeology)Metropolitan areaChinaWelfareAgricultureSocial securitySocial WelfarePensionBusinessEconomic growthHydroelectricityNatural resource economicsEconomicsGeographyPolitical scienceFinanceMarket economyEcology
DOInot available

Abstract

fetched live from OpenAlex

Involuntary resettlements induced by hydroelectricity projects (IRHP) are deeply affected by rapid urbanization in China. Therefore, the issue should be analyzed, resolved in the context of urbanization. The metropolitan area of east China should be one of the major bases for resettlements. There is possibility to displace these people out, no matter whether it is because of the ecological condition and social-economic development in emmigration areas (“push” side), or it is because of the demand for labors in the metropolitan area of east China (“pull” side). Through the case of Longtan Reservoir, a package of welfare policies and a fiscal budget in the extreme condition (permanent urban resettlement for all agricultural resettlers) are provided to show that permanent resettlement in the context of urbanization is also sufficient. The package of welfare is made of social security, 9-year financial aid for child’s education, and low renting housing system. Based on the analysis, some issues are further discussed: the way of non-agricultural resettlement for agricultural resettlers, threshold for admission to obtain urban identification (Hukou) and welfare package, professional and employment training for resettlers, and shifts from two different resettlement ways (non-agricultural and agricultural).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.371
Teacher spread0.352 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2010
Admission routes1
Has abstractyes

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