Tawhidi Scientific Research Program (Tsrp): Islamic Socio-Scientific Inquiry
Bibliographic record
Abstract
A process model is derived from the Tasbih-Shura nature of the Shuratic process (discursive process). The Tasbih-Shura dynamics is consultative and participatory, hence discursive in the light of the Qur'an. The imminent Shuratic process is thus a methodology associated with the meaning of the embryonic Shura as a discursive medium that spans across all domains of socio-scientific inquiry. The existence of such inherent and pervasive discursive dynamics is to be found in all realms of the natural and human order; in the abstraction of the seen and unseen worlds, about which the Qur’an speaks. The latter kind of world-system may be temporally revealed or may remain permanently hidden. Yet in all conditions, the monotheistic law makes all such domains profoundly interactive and integrative in the sense of knowledge-inducing human discursive experience and the participative complementary nature of the world-system. This kind of exercising effort (Ijtihad) is used to discover the conscious learning nature of all things (Tasbih). We will highlight the nature of the learning process emerging from interaction leading to integration, which is marked by different kinds of consensus, equilibrium, balance, and convergence towards the moral purpose. Finally, from such emergent interactive and integrative processes arise the evolutionary processes of extensive learning in continuum. Such an evolutionary epistemology carries the attained ontological and ontic (evidential) scale of the knowledge-centered Qur’anic universe into higher stages of moral consciousness. We note that although the Shuratic process, that is the participative complementary process of organic unity, is intrinsic in everything, yet the conception needs human comprehension for reflection and use. Thus analytical formalism is invoked.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
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".