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Record W2136438570

A Study on the Forted Village System and Rural Social Order Rebuilding of Qinling-Dabashan Area in the Middle of Qing Dynasty

2015· article· en· W2136438570 on OpenAlexvenueno aff
Luo Quan

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsEmperorOrder (exchange)Government (linguistics)Period (music)Central governmentSocial orderRural areaPolitical scienceLocal governmentAncient historyHistoryLawPoliticsBusiness
DOInot available

Abstract

fetched live from OpenAlex

Located in the border of Sichuan, Shanxi, and Hubei administrative regions, Qinling-Dabashan area(area between Moutain Qin and Mountain Daba) is generally considered hard to govern. As large numbers of immigrants flooded into this area in Kangxi and Qianlong period, social contradictions became increasingly irreconcilable, leading to the outbreak of the white lotus rebellion in early Jiaqing period, which not only posed a heavy blow to the ruling of the Qing government, but also collapsed the rural social order once in this area. Since Emperor Jiaqing took office, ways of dealing with the white lotus society had changed from simply suppress to nurturing local troops and building forted villages. Through the discussion on the building process, spatial construction, internal order, role and influence of the forted village, we can conclude that it had not only prevent the wars, but also strengthened the government’s ruling on this area, which thus became an important means for the Qing Government to preserve local ruling in turmoil periods.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0010.001
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 head0.099
GPT teacher head0.302
Teacher spread0.203 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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