Bibliographic record
Abstract
Zachar et al.’s [61] critique of Self-Other Reorganization theory (SOR) stems from misunderstandings; it does not weaken the arguments in [27]. The formal framework of Reflexively Autocatalytic and foodset-derived sets (RAFs) enables us to model the process whereby, through their interactions, a set of elements become a ‘collective self’. SOR shows how the RAF setting provides a means of encompassing abiogenesis and cultural evolution under the same explanatory framework and provides a plausible explanation for the origins of both evolutionary processes. Although SOR allows for detrimental stimuli (and products), there is (naturally) limited opportunity for elements that do not contribute to or reinforce a RAF to become part of it. Replication and cumulative, adaptive change in RAFs is well-established in the literature. Contrary to Zachar et al., SOR is not a pure percolation model (such as SIR); it encompasses not only learning (modeled as assimilation of foodset elements) but also creative restructuring (modeled as generation of foodset-derived elements), as well as the emergence of new structures made possible by new foodset- and foodset-derived elements. Cultural SOR is robust to degradation, and imperfect replication. Zachar et al.’s simulation contains no RAFs, and does not model SOR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".