MétaCan
Menu
Back to cohort
Record W3197983543 · doi:10.5539/ass.v17n9p38

Evaluation of the Types and Comprehensive Effects of Ecological Migration in China: Taking the Ecological Protection and Land Tenure Protection of Xihaigu Area in Ningxia as an Example

2021· article· en· W3197983543 on OpenAlexvenueno aff
Yizhen Xu

Bibliographic record

VenueAsian Social Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPovertyImmigrationPromotion (chess)EcologyGovernment (linguistics)Distribution (mathematics)Ecological psychologyGeographyEconomic growthPolitical scienceEconomicsPsychologyBiologyPolitics

Abstract

fetched live from OpenAlex

The ecological migration project in the Xihaigu Area of Ningxia, the first of such projects to be initiated with the longest history, is a typical example of China's ecological migration projects. Through the methods of field investigation, in-depth interviews, and examination of typical cases, the paper aims to evaluate Xihaigu's ecological migration project in the aspects of ecological restoration, poverty alleviation, income increase and social development. The conclusion is that China's ecological immigrants represented by Xihaigu's example have reached ecological improvement goals and economic and social development. At the same time, due to the government's vigorous promotion of this process, the fairness of the distribution of benefits for migrants in the earlier and later stages is slightly unbalanced, and the ecological protection awareness of the immigrants was always insufficient. The later process of immigration was relatively too fast, and ecological migration still faces further challenges.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.142
GPT teacher head0.347
Teacher spread0.205 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAsian Social ScienceSame topicClimate Change, Adaptation, MigrationFrench-language works237,207