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Record W2603551374 · doi:10.3138/jcfs.42.4.615

Urbanization and Social Identities in Jordan: The Case of Irbid

2011· article· en· W2603551374 on OpenAlexvenueno aff
Mohamed Fayez Tarawneh, Mahmood Naamneh

Bibliographic record

VenueJournal of Comparative Family Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanizationIndependence (probability theory)Ethnic groupIdentity (music)National identityField researchCollective identitySociologyGender studiesSocial identity theoryGeographyPolitical scienceEconomic growthSocial groupSocial scienceAnthropologyPoliticsLaw

Abstract

fetched live from OpenAlex

This study examines the relationship between urbanization and the development of social identities in Jordan using the anthropological methodology of conducting field research in Irbid city. The following are the main results: - Primordial tribal attachments have constantly been reproduced as basis for the urban or national identities. The major difference between identity in Irbid in both pre and post-urbanization periods was that relations between individuals became impersonal in addition to the personal ones. Individuals had ethnic, national and class affiliations beside the tribal ones. - Moreover, considering that the collective national sense prevailed before independence and before the Palestinian exodus, process of producing and reproducing a collective Jordanian national identity cannot be considered as counter practice or strategy against other groups of communities.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0220.010
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.200
GPT teacher head0.379
Teacher spread0.179 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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