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Record W4407238443 · doi:10.5430/wjel.v15n4p60

A Pragma-Stylistic Analysis of Muhammad Asad's The Road to Mecca

2025· article· en· W4407238443 on OpenAlexvenueno aff
Haroon N. Alsager, M. Aly

Bibliographic record

VenueWorld Journal of English Language · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
FundersPrince Sattam bin Abdulaziz University
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

The Road to Mecca (1954), Muhammad Asad’s autobiography, written in elegant, highly evocative English prose, is a masterpiece of literary style bursting with tenderness and thoughts emanating from a profound spiritual and existential experience. In a combination of pragmatics and stylistics, the current study explores the effectiveness of language, style and authorial illocutionary intents. The rich literary style of the text is to be understood within its larger contexts: linguistic, thematic, and emotional in addition to the physical and cultural environments. The analyzed book, in its elegant, unobtrusive and subtle style, adds a great deal to emphasizing the common humanistic factors of all civilizations. The current study focuses on the literary style of the writer and its pragmatic effects to fill in a gap in previous studies which only focused on the religious and intellectual values of Asad’s writings in general. It is an attempt to prove that The Road to Mecca is more of a work of art than a travelogue or religious proselytizing.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.331
Teacher spread0.320 · 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 designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

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