Sinkhole Microcosms: Understanding Persistence of Place Through Variable Cultivation Strategies in Northeastern Yucatán, Mexico
Bibliographic record
Abstract
Abstract Sinkholes contributed to persistent human inhabitation of the northern Yucatán peninsula of Mexico for more than two millennia. Building on previous work on the use of sinkholes central to the town of Tahcabo and elsewhere in the Maya area, this study presents pollen, soil carbon isotope, radiocarbon, and artifactual evidence from four geomorphic features. They include the perennially wet cenote situated in the town center and three dry sinkholes ( rejolladas ) located in the commonly held lands ( ejido ) of the town. These features demonstrate striking variability in multispecies engagements with and within sinkholes, especially over the past 500 years, amid colonialism and more recent political contexts. Climate and political dynamics are implicated in the observed variability in agricultural practices. Community-engaged research often embraces a focus on persistent places, which can inspire contemporary people to reconnect with the past and with ancestors in ways that promote action to address challenges, such as adaptation to climate and other environmental change. Our research addresses long histories of sinkhole use to demonstrate the outcomes of variable cultivation strategies, such as increased biodiversity within towns and places of refuge, or conversely, production intensity and accelerated soil erosion into and mixing of sinkhole sediments.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".