Investigating the Narrators from the Senior Tabi'in Class Who Narrated from Two Companions and Were Classified as "Maqbūl" by Ibn Hajar in "Taqrib al-Tahdhib"
Bibliographic record
Abstract
This research aims to identify and analyze narrators from the senior successors of the companions (Kibār al-Tābiʿīn) who narrated from two companions (Ṣaḥāba) and were classified as "acceptable (Maqbūl)" by Ibn Hajar in his work "Taqrīb al-Tahdhīb," which represents the sixth rank in his categorization of narrators' integrity. A critical gap exists in the comprehensive analysis of these narrators, particularly those who had access to multiple companions yet maintained limited transmission networks. The research addresses important methodological questions regarding how the breadth of a narrator's instructional sources influences their classification in the science of criticism and validation (jarḥ wa taʿdīl) and whether narrating from two companions provides additional credibility compared to single-companion transmission. The significance of this study lies in providing detailed insights into hadith narrators among senior successors who achieved moderate diversification in their sources while remaining in the middle ranks of narrator reliability. An inductive approach is employed to gather comprehensive information on this specific category of narrators from "Taqrīb al-Tahdhīb," tracking their narrations across various hadith collections and applying descriptive analytical methodologies to study their classifications and transmission patterns. Expected outcomes include a systematic catalog of these narrators, analysis of their role in hadith transmission networks, evaluation of their contributions to both Marfūʿ and Āthār literature, and a deeper understanding of Ibn Hajar's methodology in assessing narrators with dual-companion transmission. This research ultimately contributes to a more nuanced understanding of the transmission of prophetic traditions among senior successors, helping to clarify the significance of source diversification in narrator evaluation and its impact on hadith authentication processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".