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Record W4376504891 · doi:10.1177/24557471231169386

Factors Affecting Urbanisation in Iraq: A Historical Analysis from 1921 to the Present

2023· article· en· W4376504891 on OpenAlexaff
M. Khalis Raouf Hassan

Bibliographic record

VenueUrbanisation · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsYork University
Fundersnot available
KeywordsUrbanizationLanguage changePoliticsDevelopment economicsPopulationPolitical sciencePolitical instabilityEthnic groupPopulation growthEconomic growthPolitical economyGeographySociologyLawEconomics

Abstract

fetched live from OpenAlex

This article conducts a historical analysis of urbanisation in Iraq and identifies three factors for its unsustainability—political instability, rapid population growth and oil discovery—which are discussed and analysed. In 1930, only 25 per cent of Iraq’s population lived in urban areas. This figure rose to 71 per cent in 2020 due to rural to urban migration, forced migration and internal displacement due to ethnic and sectarian conflicts and wars. Oil has brought economic development, but it has also led to militarisation and wars, which diverted authorities’ attention from the rapid urbanisation and led them to miss opportunities to deal with it in a timely manner. A reversal of the unsustainable urbanisation in Iraq would require genuine political reform, ending corruption and preparing a national development plan that deals with the crucial challenges brought on by urbanisation.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.010
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.091
GPT teacher head0.234
Teacher spread0.143 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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