Prospects of Culture, Science and Human in the Context of a Technocratic Tide of the Post-Industrial Era
Bibliographic record
Abstract
The main aim of the study is to investigate prerequisites, essence and possible consequences of deaxiologisation trends in culture and deanthropologisation tendencies in science which arose out in the post-industrial age. Globalization processes are of a great importance in deprivation the science in its technocratic mechanistic interpretation of its historically determined constructive “human-centric” potential that had been implementing through creation and development of spiritual foundations of a human and society. The new shape of science – techno-science – exists without general metaphysical basis, summarizing and generalizable epistemological principles and person-oriented beginnings. It becomes to signify the return to mechanism in the field of implementation of logical procedures and processes but in the new – technocratic – dimension. The “new” mechanism, unlike the “classic”, is not about reducing the nature of man, society and culture to their nature-centric grounds that base and depend on physical laws, but is about orientating to extrabiological and virtual technical analogies, so it makes one to point out comprehensive competition between the human and artificial intelligence in all fields of vital activity. The main points and conclusions have their grounds on analysis of the most significant stages of science development from classics to post-non-classics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".