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Record W4410225515 · doi:10.17656/jlps.10278

Variety between regions legal systems, danger of disintegration and question about future of the Union /A philosophical study about effect of Variety between legal systems on unity and disintegration

2025· article· en· W4410225515 on OpenAlexaboutno aff
Ismail Namiq Hussein, Shilan Raouf Latif

Bibliographic record

VenueJournal of Legal and Political Studies · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Political scienceLawLaw and economicsSociologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In this research, we followed an analytical and comparative method, to study and discuss the right of the regions in the federal state to have legal system, and then we dealt with the effect of the variation between the legal systems of the regions on the future of the union. we concluded that one or more regions in the federal state may have a different legal system, this variation may be explicitly like province of Quebec in Canada, and Louisiana state in USA, or may be implicitly like South Africa, which followed a hybrid legal system. this variety between legal systems of the federal state doesn’t threat on the future of the Union, but if it is not properly handled, then the Union will be faced to danger of disintegration and abolition. In order to ensure the success of federalism in Iraq, we have proposed that a mixed legal system will be adopted in Iraq, both at the federal and regions levels, and that each region will be given the right to choose its legal system and to choose how to regulate legal relations within the borders of the region, with binding by bases, principals and purposes of the Union. Keywords: purpose of law, conflict, proximity, shariaah, sources of law.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.704
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.284
Teacher spread0.265 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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