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Record W6944243226 · doi:10.18280/ijsdp.200639

The Consequences of the Fragmentation and the Division of Residential Units: A Case Study of Ramadi City in Iraq

2025· article· en· W6944243226 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPlace Attachment and Urban Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFragmentation (computing)Division (mathematics)SubdivisionWork (physics)

Abstract

fetched live from OpenAlex

This research addresses a significant phenomenon that has become evident in many urban centers, namely the fragmentation of land plots and residential units, and the subdivision of parts of them into smaller uses that differ in shape and detail.This phenomenon has resulted in both negative and, in some cases, positive impacts.The study aims to examine the urban, organizational, economic, and social impacts resulting from this phenomenon.It is based on a comprehensive field survey methodology and the distribution of a questionnaire form, employing geographic statistical methods supported by library sources.The questionnaire was distributed to a 3% sample (227 completed questionnaires) of the total 3,772 cases experiencing fragmentation.This situation generated a substantial amount of data, as presented in the accompanying tables.The study concluded with several findings, the most prominent being that the phenomenon of fragmenting and subdividing residential units has left significant urban impacts, starting with the introduction of new building materials, modifications, vertical extensions, and a notable disparity in the city's skyline along main and local street facades within the same neighborhood or even on the same street.For example, a 4-meter skyline line appears adjacent to another that reaches more than 25 meters.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.026
GPT teacher head0.343
Teacher spread0.316 · 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.

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
Published2025
Admission routes1
Has abstractyes

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