MétaCan
Menu
Back to cohort

Land degradation and population relocation in Northern China

2012· article· en· W1489429835 on OpenAlexaff
Chong Dong, K. K. Klein

Bibliographic record

VenueAsia Pacific Viewpoint · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversity of Lethbridge
FundersGovernment of Jiangxi Province
KeywordsOvergrazingRelocationChinaGrassland degradationGeographySocioeconomicsHousehold incomeDesertificationLand degradationEconomic interventionismPopulationEnvironmental degradationGovernment (linguistics)GrazingEnvironmental protectionEcologyEnvironmental healthEconomicsAgriculturePolitical science

Abstract

fetched live from OpenAlex

Abstract Overgrazing in the grasslands of Inner Mongolia following market reform in China has led to severe soil degradation and desertification. In an effort to revive the ecological environment in northern pastoral areas, the government of China recently adopted an intervention policy to relocate families from areas where excess grazing pressure was seriously compromising land and the environment. A survey was conducted in three villages to determine how well the relocated families have adapted to their new living conditions and the factors that affect their willingness to stay in the new villages. Regression analysis revealed that the most important factors were age of the head of the household, length of time the family has resided in the new village, proportion of total income that is made up of government payments and level of fixed, durable and current assets.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.093
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations14
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueAsia Pacific ViewpointSame topicRangeland Management and Livestock EcologyFrench-language works237,207