The Beasts At Large – Perennial Questions and New Paradigms for Caribbean Translocation Research. Part II: Mammalian Introductions in Cultural Context
Bibliographic record
Abstract
Looking to clarify outstanding questions about human-animal dynamics in the pre-Columbian Caribbean, archaeologists have recently renewed investigation into the sociocultural context of mammal translocations to the islands. In this second instalment of a three-article series, I examine Amerindian ethnophoresy, that is, the process of anthropogenic species dispersal and its associated cultural practices, drawing on archaeological, ethnographic, and ethnohistoric evidence. Building on the ethnozoogeographic baselines established in Part I, I consider the tangible and intangible roles of introduced mammals, with particular attention given to subsistence, status, symbolic and ritual dimensions. I discuss enduring speculation over the management and incipient domestication of these species and its broader significance. Collectively, these topics are important because they inform explanation of the cause, extent and consequences of non-native animal introductions and allow us to understand translocation as an adaptive response to the natural and cultural environment. I conclude that resolution of the managed/domesticated status of non-native animals, in particular, constitutes the most critical research area in Caribbean ethnophoresy since this bears directly on the environmental impact and ecological legacy of mammal introductions in the region. This last topic is addressed in Part III of the series.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".