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Record W4388701560 · doi:10.5539/jpl.v16n4p43

Multi-Ethnic Society and Lack of Political Culture in Afghanistan

2023· article· en· W4388701560 on OpenAlexvenueno aff
Osman Mohammed Afzal

Bibliographic record

VenueJournal of Politics and Law · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupPoliticsRivalryAutocracyPolitical economyPolitical scienceDevelopment economicsEthnic conflictLegitimacyDemocracySociologyLawEconomics

Abstract

fetched live from OpenAlex

Ethnic diversity and ethnic politics in Afghanistan overcome the common political culture that the nationalities have never been coherent regarding political decisions in the country. The only issue that led the nationalities to cohesiveness is religion as the common value and culture. Except for religion, the other commonalities do not highly influence the cohesiveness of the nationalities in Afghanistan. Thus, religion often brought together nationalities against foreign factors and withstanding interventions; however, concerning inner challenges and conflict, religion has never been a factor in diminishing and resolving inner conflict. The legitimacy of regimes and fair schemes for the welfare and the status quo change is not the fundamental issue for ethnicities in Afghanistan. Still, the extent of ethnic political participation in the government has often been considerable. The central government and centralised regime led to a big rift in the society and led to rivalry at any cost among the ethnicities to hold further political authority. The autocracy under the definition of Democracy, at least within the last 20 years in Afghanistan, one way or another, even changed the social norm among ethnicities that everyone, instead of feeling responsibility toward the government and national interest, focused on ethnic interests.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.385
Teacher spread0.308 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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