MétaCan
Menu
Back to cohort
Record W3169721141 · doi:10.5509/2021942347

Suspension 2.0

2021· article· en· W3169721141 on OpenAlexvenueno aff
Yang Zhan

Bibliographic record

VenuePacific Affairs · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsnot available
FundersTsinghua University
KeywordsSpeculationLivelihoodChinaState (computer science)PopulationInvestment (military)Capital (architecture)BusinessCompensation (psychology)Development economicsMarket economyEconomic growthFinanceGeographyPolitical scienceEconomicsSociologyLawAgriculture

Abstract

fetched live from OpenAlex

Since the late 2000s, many rural-to-urban migrants in China have lost their rural land to development plans, resettled in designated areas, and acquired formal urban residency. They stopped migrating, and have apparently ended their life of "suspension," namely protracted mobility. While most existing research literature on this population foregrounds the issue of land dispossession, this article argues that, following resettlement, these former migrants' lives can be more accurately characterized as a state of suspension instead of dispossession. Many resettled young adults, while having secured livelihood thanks to state compensation, are excluded from the technology- and capital-intensive developments to which they have lost their land. Some of these young people instead became petty speculators and rentier capitalists by liquidating their compensated assets through mortgages, private lending, rent, and other financial means. They are constantly waiting for the next investment opportunity and windfall gain. Although physically settled down and economically secure, they remain anxious and unsettled. They continue to orient their lives towards an elusive future rather than striving to transform the here and now, thus living in a state that I call "suspension 2.0."

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score1.000

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)0.0010.000

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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.

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

Citations9
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePacific AffairsSame topicChina's Socioeconomic Reforms and GovernanceFrench-language works237,207