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Record W3138325062 · doi:10.53762/xrxkkf48

10.53762/xrxkkf48

2000· article· en· W3138325062 on OpenAlexvenueno aff
Huma Ejaz, Musferah Mehfooz, Muhammad Iqbal

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceBusiness

Abstract

fetched live from OpenAlex

Lately, the very role of Islamic institutions of higher learning known as Madrasās particularly in Pakistan has been in the debate at national as well as international levels. Some consider these seminaries as the citadels of Islam; and some view them as sources of hatred, extremism, activism, fanaticism, and terrorism. The argument advanced in favour of the role of Islamic centers of learning is that their end-products serve the society as muftis, sharīʻah court judges, religious teachers, Qadīs for the marriage ceremony, preachers, imāms of mosques, and mu’azzins for prayers. It is claimed that Pakistan without these Madrasās will lose its face as an Islamic nation, on the one hand, and Muslims will stand deprived of the services of the most needed personnel in the socio-religious arena, on the other. The motivation to work in Madāris is the thought pattern of the modern studies which enable us to have an insight into how critical and vulnerable is the education given at Madāris of Pakistan. Blame game against Islamic institutions is for sure to pour petrol on the fire, so the problem needs to be tackled wisely. This study is aimed at delving into the system of education involving both curricula and the methodology of teaching and learning in Madāris and suggesting ways to overcome the underlying problems. The findings of the study may prove a catalyst in making Madāris education boon and not bane for the beloved country.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.498
Threshold uncertainty score0.186

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9960.982

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 head0.265
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2000
Admission routes1
Has abstractyes

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