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Record W4407390927 · doi:10.1080/03068374.2024.2446960

GOVERNANCE AND PUBLIC ADMINISTRATION UNDER THE TALIBAN

2025· article· en· W4407390927 on OpenAlexfundno aff
Waheedullah Hamoon, Bohdan Krawchenko, Tamara Krawchenko

Bibliographic record

VenueAsian Affairs · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsAdministration (probate law)Corporate governancePublic administrationPolitical scienceBusinessLawFinance

Abstract

fetched live from OpenAlex

The Islamic Emirate of Afghanistan (IEA), also known as the Taliban, took over Afghanistan in August 2021 after a rapid military campaign. Unlike the first Taliban regime (1996–2001) that took power when the state was in ruins during the civil war that erupted after the USSR left the country, the second Taliban administration inherited a reasonably well-developed civil service, the first of its kind in the country's history with modern budgeting, accounting, reporting, and digitalization systems, that played an essential role in modernization, including advancing women's rights. The Taliban have taken the state apparatus as an instrument of their governance approach, which is rooted in their specific religious ideology. This paper explores the Taliban's governance strategies and theocratic control mechanisms and their implications for public administration and economic development. Through a literature review, document analysis, and interviews with Afghan civil servants, this study explores civil service structure, remuneration, leadership, funding priorities, revenue collection, and the role of NGOs and humanitarian aid. The findings shed light on the challenges faced by the Taliban in fostering a viable economy within the constraints of a theocratic regime with limited governance capacities and no clear development strategy.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.288
Teacher spread0.273 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2025
Admission routes1
Has abstractyes

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