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Cultivating an Ecological and Social Balance: Elite Demands and Commoner Knowledge in Ancient Ma‘ohi Agriculture, Society Islands

2011· article· en· W2125609201 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Anthropologist · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCommonerEliteAgricultureEthnographyBalance of natureAgricultural productivityProductivityEcologySociologyGeographySocial scienceArchaeologyEconomic growthPolitical sciencePoliticsBiologyEconomicsLaw

Abstract

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ABSTRACT Anthropological views of past human–environmental interactions are influenced by the data sets used and the subjects of study. In this article, we seek a balanced view of ancient human–environmental interactions in the Society Islands. We explore the social and ecological contexts of agricultural production by incorporating archaeological and ethnographic data as well as the motivations and actions of Ma‘ohi elites and commoners. Both elites and commoners contributed to long‐term agricultural productivity. The elite did so through periodic restrictions on harvesting; the farmers contributed ecological knowledge acquired through generations of on‐the‐ground experience. Our fine‐scale examination of the archaeological remains of three agricultural systems in the ‘Opunohu Valley indicates that the roles of elite and commoner played out differently depending on their social‐spatial proximity. By refocusing our analyses on all players in the production system, a more nuanced understanding of the range of ancient environmental and social interactions emerges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.028
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.340
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it