Przyczyny wymierania grup etnicznych Nowego Świata
Bibliographic record
Abstract
The article presents the second part of the results of a study on the causes of the extinction or assimilation of ethnic groups of the so-called “new world” that took place after 1924, i.e. in the last 100 years. A method of systematic cataloguing of scientific literature, mainly ethnographic, historical, linguistic and political science, was used to collect all the causes, and, in the absence of availability of such, media reports were drawn upon. The fact that the extinction of ethnic groups has greatly accelerated in the past three decades was noted. Perhaps surprisingly, the extinction was noted mainly in the democratic states of the so-called “new world”, which are regarded as protecting the rights of minorities: the United States, Australia, Canada and others (see the first part, volume 50). More than 100 extinct peoples in 100 years is not a good prognosis for the struggling survival of numerically small ethnic groups, of which there are many. All catalogued cases are shown on a world map and the main causes of their extinction are listed, ranked from most common to individual. Preventing these causes can save the world from reducing the cultural and genetic diversity of mankind.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".