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Record W3209308898 · doi:10.18280/ijdne.160512

Bias in the Critique of Arab Architecture

2021· article· en· W3209308898 on OpenAlexvenueno aff
Hasanain A. Karbol, Sarah M. Al-Saadi, Basim Hasan Hashim Al-Majidi

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsnot available
Fundersnot available
KeywordsCriticismArchitectureIdentity (music)EpistemologyPoliticsSubject (documents)SociologySet (abstract data type)Mechanism (biology)Point (geometry)Computer scienceAestheticsPolitical scienceHistoryLawMathematicsPhilosophy

Abstract

fetched live from OpenAlex

The research derives its significance from the importance of the subject of architectural criticism, and what it reflects on the reality of contemporary architecture and local identity in the Arab region in light of the changing political and economic ideas. From this point of view, the research problem can be summarized as: The extent of the comprehensiveness of previous studies of the relationship of bias to architectural criticism and determining its characteristics and types as a mechanism of criticism in contemporary Arab architecture. To address the research problem, the goal of the research was determined by building a theoretical framework to understand how to release critical judgments within the concept of bias, and to access the mechanisms that measure criticism in contemporary Arab architecture based on the research hypothesis that states: The intellectual features in architectural criticism are determined through a set of characteristics and concepts associated with the concept of bias.

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)0.019
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0060.047
Scholarly communication0.0100.007
Open science0.0010.005
Research integrity0.0030.003
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Design & Nature and EcodynamicsSame topicArchitecture and Cultural InfluencesFrench-language works237,207