Bibliographic record
Abstract
Hace mas de diez anos comence a reflexionar sobre como la sociologia esta tomando a America Latina como un objeto de estudio. A partir de ese momento, mi objetivo fue adquirir mas conocimiento sobre la sociologia latinoamericana afin de comprender como esta ciencia ha representado dicha region y como esta participando en su transformacion. A un nivel mas conceptual, estuve interesado en saber como esta disciplina selecciona los problemas sociales y sugiere cambios. Finalmente, esto me ayudo a forjarme opiniones sobre el conocimiento y las ciencias sociales. Por muchas razones, algunas de ellas presentadas a lo largo de este texto, considero que America Latina deberia estar protegida de la problematizacion sociologica o del proceso por el cual los fenomenos sociales son representados en terminos de problemas. Aqui, me gustaria reflexionar sobre la ciencia social y la sociedad. Esto no como un resumen de mis principales resultados, sino como una excusa para discutir sobre la problematizacion sociologica en America Latina. Permitame comenzar resumiendo brevemente algunos de mis resultados de investigacion y entonces reflexionar sobre la problematizacion y el colonialismo del conocimiento. Para esto, intentare contestar a la pregunta: ?Deberiamos proteger America Latina contra la sociologia?
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".