Undergraduate teaching of evolution in chile: more than natural selection
Bibliographic record
Abstract
In a recent commentary, Nespolo (2003) makes reference to his personal experience as exattendant to the course of evolution imparted by Dr. Humberto Maturana and Dr. Jorge Mpodozis at the Facultad de Ciencias of the Universidad de Chile to construct a negative criticism of Chilean undergraduate teaching of evolution. As ex-attendants of the mentioned course of evolution we have had an experience that is directly comparable to that of Dr. Nespolo. Here we wish to point out our opinion regarding this course, which is markedly different. First, it is a caricature to state that in this course natural selection is taught as being wrong. A serious and critical revision of natural selection, the synthetic theory, and evolutionary ecology is a fundamental part of the course. These and other topics are presented by researchers from those fields, such as Drs. German Manriquez and Rodrigo Medel. The scientific contributions of both researchers receive positive comments in Nespolo (2003).
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".