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Record W7128688242 · doi:10.26180/4663903.v1

Pakana Maleetye: art and the survival of indigeneity within the Aboriginal Community of Nicholls Rivulet, Tasmania

2017· dissertation· W7128688242 on OpenAlexaboutno aff
Joel Stephen Birnie

Bibliographic record

VenueMonash University · 2017
Typedissertation
Language
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDepictionIdentity (music)ColonisationTraditional knowledgeCultural identityEthnically diverseMetis

Abstract

fetched live from OpenAlex

In this thesis I have researched the evolution of the Indigenous community of Nicholls Rivulet, South East Tasmania between the periods 1850-1950. I have examined the recorded oral histories, academic publications and historical records to create an overall picture of how the community retained their unique Indigenous and cultural identity. Each chapter explores the foundation of Indigenous identity within Tasmania. The topics range from the creation of an ethnically mixed Indigenous community, to the depiction of Indigenous Tasmanians by academics and artists in the later years of colonisation and to the powerful and challenging response to historical and cultural lies by contemporary Tasmanian Aboriginal artists. Armed with the knowledge gained by this research, I then express my personal response to this history within my artwork. From my experiences visiting the traditional lands of my family to my exploration of Indigenous identity from a cultural, familial and personal perspective.

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)0.001
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 score0.170
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.009
Scholarly communication0.0030.001
Open science0.0010.003
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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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