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Record W7025369333

In whose interests?: media, political communication and First Nations Australians

2018· other· en· W7025369333 on OpenAlexaboutno aff

Bibliographic record

VenueQueensland's institutional digital repository (The University of Queensland) · 2018
Typeother
Languageen
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPoliticsClosing (real estate)Corporate governancePolitical communicationPublic policy
DOInot available

Abstract

fetched live from OpenAlex

This chapter examines the interlocking fields of media and political representation, public policy and perception, and the public interest as it relates to First Nations Australians. It focuses on several key questions raised in the Closing the Gap issues paper, cited above, which argues that Australia lags behind other similarly developed settler countries - notably New Zealand, the United States and Canada - in implementing sustainable governance policies, mutually determined between governments and its Indigenous peoples. The chapter examines how the interests of Australian Indigenous peoples fare in terms of media and political representation, communication management, public policy, and social perception. It explores key themes of participation, accountability, understanding and agency, and looks at how these line up with acceptable expectations of the public interest. The chapter explores the apparent disconnect between what is in the interests of Indigenous peoples, and popularised notions of the national public interest.

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)0.004
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.009
Scholarly communication0.0100.009
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.039
GPT teacher head0.292
Teacher spread0.253 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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