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Record W603824579 · doi:10.7146/mog-ms.v42.150097

Orientation systems of the North Pacific Rim

2011· article· en· W603824579 on OpenAlexaboutno aff
Michael Fortescue

Bibliographic record

VenueMeddelelser om Grønland. · 2011
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)GeographyArcticOrientation (vector space)GeologyThe arcticArchaeologyOceanographyGeometry

Abstract

fetched live from OpenAlex

Orientation Systems of the North Pacific Rim is an extension of the author’s earlier volume Eskimo Orientation Systems (also published in the series Monographs on Greenland | Meddelelser om Grønland, Man & Society, 1988). This time it covers all the contiguous languages – and cultures – across the northern Pacific rim from Vancouver Island in Canada to Hokkaido in northern Japan, plus the adjacent Arctic coasts of Alaska and Chukotka. These form a testing ground for recent theories concerning the nature and classification of orientation systems and their shared ‘frames of reference’, in particular the many varieties of ‘landmark’ systems typifying the Arctic and sub-Arctic. Despite the wide variety of languages spoken here (all of them endangered), there is much in common as regards their overlapping geographical settings and the ways in which terms for orientation within the microcosm (the house) and within the macrocosm (the surrounding environment) mesh throughout the region. This is illustrated with numerous maps and diagrams, from both coastal and inland sites. Attention is paid to ambiguities and anomalies within the systems revealed by the data, as these may be clues to pre-historic movements of the populations concerned – from a riverine setting to the coast, from the coast to inland, or more complex successive displacements. Cultural factors over and beyond environmental determinism are discussed within this broad context.

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.

How this classification was reachedexpand

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.061
GPT teacher head0.325
Teacher spread0.264 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2011
Admission routes1
Has abstractyes

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