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Record W6967728826 · doi:10.5281/zenodo.13292418

From Calcutta Madrasaḥ to 'Āliah University: A Journey

2024· article· en· W6967728826 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBENGALGovernment (linguistics)PrestigeIslamInstitutionQuarter (Canadian coin)Administration (probate law)Educational institutionPromotion (chess)

Abstract

fetched live from OpenAlex

The history of Muslim education in India since the inception of British rule, is closely associated with the history of Calcutta Madrasaḥ popularly known as Madrasaḥ-e-ʿĀliah. It is the main spring from and round which a system of madrasaḥ education grew up in India. The Calcutta Madrasaḥ was the first educational institution in India, established by the British Government for the promotion of education in Theological Science, Oriental Studies, Medical Education, Geological Studies and Islamic Laws among the Muslims of Bengal for the purpose of administration and the judiciary. The institution which has managed to cover such a time period of two and a quarter century has played a remarkable role in the dissemination of knowledge, as well as social and cultural activities. It was hugely affected by the partition of the Indian subcontinent in 1947 and lost its earlier prestige and status. Then, owing to continuous movements by the students of the madrasaḥ and votaries of madrasaḥ education, against the ruling government of West Bengal to establish their tradition through this educational Institution, the Calcutta Madrasaḥ regained its college status and then has been upgraded to ʿĀliah University in 2007. This paper traces the journey for this institution.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0480.011
Scholarly communication0.0140.005
Open science0.0020.013
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0120.002

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 head0.059
GPT teacher head0.309
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; 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicEducation and Islamic StudiesFrench-language works237,207