Bibliographic record
Abstract
La palabra “Etnicidad”, para el autor de este articulo, es un concepto de difícil aplicación a las poblaciones vivientes, esto debido a la naturaleza dinámica y a las complejas relaciones de las identidades sociales, que incluyen religión, nacionalidad, estatus y ascendencia. Etnicidad es también un término contextual y fluido relativamente nuevo, antropológicamente hablando: evolucionó a mediados del siglo XX, a partir del rechazo del concepto de raza. Los antropólogos reconocieron que existe una preponderancia de las características culturales sobre los rasgos biológicos y por ende, la etnicidad se convirtió en un tapiz de fibras sociales. Se analizan además las caracristicas subjetivas y objetivas de la Etnicidad teniendo en cuenta la importancia de este factor dentro de la sociedad, tomando aclaraciones e investigaciones de diferentes antropólogos contemporanéos y arqueólogos que son cautelosos en el uso del concepto de «etnicidad», que a menudo es muy complicado para un uso práctico como herramienta de análisis .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".