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Record W4210271794 · doi:10.52337/pjia.v4i4.333

HISTORY AND BACKGROUND OF MADRASSAH EDUCATION IN PAKISTAN

2021· article· en· W4210271794 on OpenAlexaboutno aff
Surriya Shahab

Bibliographic record

VenuePakistan Journal of International Affairs · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamIslamic fundamentalismAncient historyPolitical scienceGovernment (linguistics)PopulationPoliticsQuarter (Canadian coin)HistoryGeographySociologyLawDemographyArchaeology

Abstract

fetched live from OpenAlex

Pakistan has been traditional and modern education systems since its inception. The traditional education system or traditional Islamic schools which are called Madaris (Madrassahs) have been growing rapidly since 1980s during the Soviet intervention into Afghanistan and Imam Khumeni Revolution in Iran. The madaris have been influenced by the wave of Islamic fundamentalism from Iran and Afghanistan. After the Taliban Government in Afghanistan in late 1990s, the Deoband Madaris in Pakistan came gradually under the sway of the anti-West Taliban Movement. In 2000, there are more than 50,000 Madrassahs in Pakistan but only 4,350 were registered. The history of Madrassahs education in Pakistan has been originated by the advent of Islam and Arabic culture to India with conquering of Sindh by Muhammad bin Qasim in 712 A.D. After the formation of Muslim rule at Delhi in 1208 A.D., a quarter of Indian-subcontinent population had converted to Islam over the next five centuries and Madrassahs were established in India. Those madaris had been providing education among Muslims of India from 1208 A. D. to 1757 A. D. till the British power in India. The Madrassahs in Pakistan are alleged to be nurseries to produce religious extremists. The purpose of this paper is to highlight the history and the changing pattern of Madrassahs Education in Pakistan. The paper is also examining the socio-political framework of Pakistan under which the Madrassahs are working.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.366
Teacher spread0.342 · 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
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

Citations4
Published2021
Admission routes1
Has abstractyes

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