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Record W4411396337 · doi:10.53762/d4d0mk90

10.53762/d4d0mk90

2000· article· en· W4411396337 on OpenAlexvenueno aff
Abdullah Saghir Aasi, Asjad Ali, Nasmiati

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamStyle (visual arts)Character (mathematics)Field (mathematics)SociologyHumanitiesPsychologyHistoryPhilosophyArtTheologyLiteratureMathematics

Abstract

fetched live from OpenAlex

This article deals with character-building of Pakistani women in the light of the style of Dawa’h and training of Saḥābiyāt. It argues that male and female Companions of the Prophet of Islam always kept in mind the guidance and behavior of the Messenger of Allah, in Dawa’h and preaching. In the present era many Muslim men and women are doing Dawa’h and Tablāgh. Women are contributing a lot in this field, but the method of the contemporary women mostly are unfamiliar with the methodology of Saḥābiyāt in this regard. This research maintains that it is very important for Dawa’h workers to be well aware of the requirements of the modern age and the resources available in the field. This paper concludes that today’s women should follow the examples of Saḥābiāt in the field of Dawa’h specially the example of Hazrat Ayisha Siddiqa.

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 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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.021
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9790.978

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 spread0.250 · 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; the direct Gemma label and the distilled Codex classifier 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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