Blindness: physical or spiritual? An attempt at an interdisciplinary analysis
Bibliographic record
Abstract
This article focuses on the issue of the weakness of human perception, which raises questions about the reasons for not recognising certain people and the mistakes related to such, at the level of both the physical and spiritual senses. The main issue here is why we do not recognise the face and figure of another person. One of the classic examples of this phenomenon is the meeting of Jesus with his disciples on the road to Emmaus (Lk 24:13–35), where first Jesus is inexplicably unnoticed by the disciples, and then unrecognised. We attempt an interdisciplinary analysis of this event. Theological interpretations of the causes of this disability (e.g. as the effects of original sin) are insufficient, which is why they are supplemented with philosophical and anthropological interpretations, as well as contemporary empirical research on facial recognition conducted in the area of psychology. The article arrives at the conclusion that the results of the research on the defects in the mechanisms of perception found by psychologists, and a philosophical, as well as theological, analysis of human nature and theology do not contradict each other, but rather create a more complex (exhaustive) answer to the question posed. Intradisciplinary and/or interdisciplinary implications: A strictly theological interpretation of human behaviour stems from original sin in that it has damaged human nature by constricting its cognitive abilities. This article goes beyond such a restrictive approach in exploring this absence of vision by including both the philosophical and empirical approaches used in psychology.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".