MétaCan
Menu
Back to cohort
Record W4285726092 · doi:10.2993/0278-0771-42.2.217

Digging Deep: Place-Based Variation in Late Pre-Contact Mā‘ohi Agricultural Systems, Society Islands

2022· article· en· W4285726092 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

VenueJournal of Ethnobiology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEliteAgricultural productivityCommonerAgricultureGeographyArchaeological recordArchaeologyEthnologySociologyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Understanding the social and ecological contexts of past agricultural systems in complex societies requires expansive and nuanced data sets that recognize the role of all players in the production system. Such data sets are not often available and thus, there is a tendency to generalize across polities and ecosystems and to homogenize place- and time-specific variation. Here, we bring together ethnohistoric, ethnographic, and archaeological data to explore Mā‘ohi commoner and elite involvement in the production systems of the Society Islands at the time of European contact (AD 1767). We focus our analysis on the archaeological records of five polities located in four different watersheds on the islands of Mo‘orea and Ra‘iātea. We divide the polities into those that are elite- vs. commoner-centric and those that are located in productive versus marginal agricultural landscapes. We find that elites have a greater presence and closer association with agricultural production in productive ecological settings than in the more marginal ones. Although the archaeological expression of the agricultural systems look superficially the same in all contexts, maintaining productivity in the marginal contexts would have required different knowledge and more effort on the part of the Mā‘ohi farmer than in the more productive settings. In contrast to previous summaries of Mā‘ohi agriculture that focus on elite control and seasonal shortages, we highlight the place-based knowledge of Mā‘ohi commoners that was foundational to the centuries-old production systems that provisioned both the elite and commoners alike.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.277
Teacher spread0.259 · 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