Applied Montology Using Critical Biogeography in the Andes
Bibliographic record
Abstract
More than most other landforms, mountains have been at the vanguard of geographical inquiry. Whether promontories, cultural works on slopes, or even metaphorical/spiritual heights, mountain research informs current narratives of global environmental change. We review how montology shifts geographic paradigms via the novel approach of critical biogeography in the Andes. We use it to bridge nature and society through indigenous heritage, local biodiversity conservation narratives, and vernacular nature–culture hybrids of biocultural landscapes (BCLs), focusing on how socioecological systems (SES) enlighten scientific query in the Andes. In our Andean study cases, integrated critical frameworks guide the understanding of BCLs as the product of long-term human–environment interactions. With situated exemplars from place naming, wild edible plants, medicinal plants, sacred trees, foodstuffs, ritualistic plants, and floral and faunal causation, we convey the need for cognition of mountains as BCLs in the Anthropocene. We conclude that applied montology allows for a multi-method approach with the four Cs of critical biogeography, a model that engages forward-looking geographers and interdisciplinary Andeanists in assessments for sustainable development of fragile BCLs in the Andes.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.006 | 0.042 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".