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Record W3147535569 · doi:10.1007/978-94-6265-431-0_14

Urbanization, Megacities, Constitutional Silence

2021· book-chapter· en· W3147535569 on OpenAlexaff
Ran Hirschl

Bibliographic record

VenueEuropean yearbook of constitutional law · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicImmigration Law and Human Rights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMegacityUrbanizationGeopoliticsSilenceGeographyEconomic geographyPopulationUrban agglomerationDevelopment economicsPolitical scienceEconomyEconomic growthSociologyDemographyEconomicsPoliticsArtLaw

Abstract

fetched live from OpenAlex

Urban agglomeration is one of the most significant demographic and geopolitical phenomena of our time. The figures are striking. In 1900, approximately 150 million people, fewer than 10% of the world population, lived in cities.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.008
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.025
GPT teacher head0.242
Teacher spread0.217 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueEuropean yearbook of constitutional lawSame topicImmigration Law and Human RightsFrench-language works237,207