Technologies and Species Transitions: Polanyi, on a Path to Posthumanity?
Bibliographic record
Abstract
Polanyi and Transhumanism both place technologies in pivotal roles in bringing about Homo sapiens ’ species transitions. The question is asked whether Polanyi’s emphasis on the role of technology in Homo sapiens’ rise out of mute beasthood indicates that he might have been inclined to embrace the Transhumanist vision of Homo sapiens’ technological evolution into a postbiological, techno-cyber species. To answer this question, some of the core commitments of both Transhumanism and Polanyi’s postcritical philosophy are examined, especially as they bear on Homo sapiens’ species transitions. The conclusion reached is that rather than being the next step dictated by the inner logic of Polanyi’s thought, Transhumanism is actually the final conclusion of epistemological ideals he spent most of his career denouncing.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.009 | 0.019 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".