Moral Singularity, Consciousness, and Artificial Intelligence in The Algorithmic Age of Islamic Economics, Finance, Society, and Science
Bibliographic record
Abstract
This paper analytically argues that received scientific doctrine and Islamic scholarship, by being methodologically independent of the principle of pairing the moral and material essence of events, have left a significant gap in understanding reality. Such a gap is referred to as exogenously independent, that is, as existing merely as a moral singularity in the methodological worldview of knowledge that otherwise pervades “everything.’ This latter essence pronounces the central role of Tawhid as the pervasiveness of the conscious continuum. The pervasive nature of the conscious continuum in Tawhidi unity of knowledge brings out the analytical power to explain the core of the socio-scientific methodology of pairing (complementarities). This study derives a logical formal model of the interrelations between the centerpiece of the unity of knowledge, consciousness, configuration of epistemic moral-materiality, and socio-scientific intellection in the post-modern algorithmic age. For example, this vastness is inherent in the new epistemic configuration of the AI regime of the algorithmic age. Such an intellectual vista of divinely induced formal inherences in the order of reality is pointed out in this paper as pertaining to the new episteme of socio-scientific moral-materiality holism. A comparative methodological approach was used. The emergent subtle areas of discourse form the originality of the paper, its focus, and its theme.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.030 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".