Atypical development spectra considering the hunter-breeder culture transition
Bibliographic record
Abstract
The different types of atypical development manifest themselves in deviations in the development and operation of neurological functions involved in the process called neurological maturation. We assume that what is called neurological maturation is in effect dependent on the cultural development of homo sapiens. Our culture changes and evolves over time. In the past, the skills and abilities of our hunter-gatherer ancestors with being a mainly oral culture is significantly different from the agricultural, stockbreeder, farmer lifestyle coupled with a mainly written culture. Each of these very distinct cultural styles require different behaviour and cognitive functions. In this article, we discuss how the increased prevalence of learning and control difficulties, along autism, may be a result of the vulnerability of the cerebral functions which from the perspective of human development count as very new. However, this may be only one aspect of a very complex story, as what may present as difficulties in one cultural norm may be strengths in another cultural norm. Many types of the specific learning difficulties, ADHD, autism spectrum disorders are getting more frequent specialties, and their becoming more frequent is the consequence of the effect of the dramatically changing environment on the brain development. While autism and dyslexia spectra seem to be the ends of a continuum, they may be rather a result of a diffused neurological development, where in contrast to the typical development, the culturally new areas are mixed over- or under-functioning.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".