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Record W2086222532 · doi:10.1080/14649365.2010.508598

Stories of crossings and connections from Bawaka, North East Arnhem Land, Australia

2010· article· en· W2086222532 on OpenAlexaff
Kate Lloyd, Sandie Suchet‐Pearson, Sarah Wright, Lak Lak Burarrwanga

Bibliographic record

VenueSocial & Cultural Geography · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsGeographyArchaeologyEconomic geographyHistorySociology

Abstract

fetched live from OpenAlex

This paper engages with Indigenous peoples' conceptualisations of borders, arguing that these unsettle dominant Eurocentric constructs of the border as terrestrial, linear, bound and defined through western legal frameworks. It does this by drawing on one aspect of the many storytelling experiences offered by members of the Indigenous-owned Yolngu tourism business Bawaka Cultural Experiences in northern Australia. We argue that stories told to visitors about multiple and diverse connections between Yolngu and Makassan people from Sulawesi, Indonesia, are intentional constructions which challenge dominant conceptions of Australia as an isolated island-nation. The stories redefine the border as a dynamic and active space and as a site of complex encounters. The border itself is continuously recreated through stories in ways that emphasise the continuity and richness of land and sea-scapes and are based on non-linear conceptions of time. The stories invite non-Indigenous people to engage with different kinds of realities that exist in the north and to re-imagine Australia's north as a place of crossings and connections.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.002
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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations25
Published2010
Admission routes1
Has abstractyes

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