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Land degradation and population relocation in Northern China

2012· article· en· W1489429835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
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