Biocultural homogenization in elementary education degree students from contrasting ecoregions of Chile
Bibliographic record
Abstract
Biocultural homogenization is a wicked problem that implies the loss of biological and cultural diversity at different scales. It is promoted by globalized one-dimensional ways of thinking that ignore the biophysical and cultural singularities of the heterogeneous regions of the planet. In Chile, we find ecoregions as diverse as the arid Norte Grande, the semi-arid Mediterranean Metropolitan region, and the temperate rainforests in the south. We studied the perceptions that elementary education degree students (EEDS) have regarding the flora and fauna (co-inhabitants), their environments (habitats), and their daily customs or activities (habits) in these three ecoregions. We distributed 72 questionnaires to students from 3 universities in 2021, asking them about co-inhabitants, habitats, and habits. We identified similarities and differences between the responses. Similarities were associated with biocultural homogenization processes evidenced by the prevalence of vertebrate animals and vascular plants, or introduced species, such as domestic animals, and cultivated plants for edible, ornamental, and medicinal purposes. Differences were associated with biocultural conservation processes such as the collection of native species of mushrooms, plants and animals for food use, or the knowledge of ritual celebrations typical of their localities. We propose that teaching study programs should aim to redirect biocultural homogenization processes toward biocultural conservation processes. That way teachers can play a key role in teaching future generations to learn and value both local and scientific knowledge about the diversity of co-inhabitants, habitats, and the life habits in each of their ecoregions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".