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Record W4286282529 · doi:10.14430/arctic75292

Yellowknives Dene and Gwich’in Stellar Wayfinding in Large-Scale Subarctic Landscapes

2022· article· en· W4286282529 on OpenAlexafffundvenueabout
Chris M. Cannon, Paul Herbert, Fred Sangris

Bibliographic record

VenueARCTIC · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsGovernment of Northwest Territories
FundersArctic Institute of North AmericaAurora Research InstituteNational Science Foundation
KeywordsSubarctic climateArcticScale (ratio)GeographyLegibilitySchema (genetic algorithms)Computer sciencePhysical geographyGeologyCartographyArchaeology

Abstract

fetched live from OpenAlex

Indigenous systems of stellar wayfinding are rarely described or robustly attested outside of maritime contexts, with few examples reported among peoples of the high Arctic and some desert regions. However, like other large-scale environments that exhibit a low legibility of landmarks, the barrenlands of the Northwest Territories and the Yukon Flats of Alaska generally lack views of prominent or distinguishing topography for using classic route-based navigation. When travelling off trails and waterways in these respective inland subarctic environments, the Yellowknives Dene and the Alaskan Gwich’in utilize drastically different stellar wayfinding approaches from one another while essentially sharing the same view of the sky. However, in both systems the use of celestial schemata is suspended in favor of route-based navigation when the traveller intersects a familiar geographical feature or trail near their target destination, suggesting strong preference for orienting by landmarks when available. A comparison of both wayfinding systems suggests that large-scale environments that lack a readily discernible ground pattern may be more conducive to the development and implementation of a celestial wayfinding schema when combined with other influential factors such as culture, individual experience, and travel behavior. These are likely the first stellar wayfinding systems described in detail for any inland subarctic culture.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations1
Published2022
Admission routes4
Has abstractyes

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