Reclaiming identity and territory: events and indigenous culture
Bibliographic record
Abstract
This chapter reviews the socio-cultural benefits and impacts of Indigenous festivals, along with the politics of Indigenous identity and cultural authenticity at events. It begins by reviewing research on the socio-cultural, economic and political impacts of hallmark Indigenous festivals in Mexico, Sweden, Canada, New Zealand, Papua New Guinea, and Australia. The chapter then focuses on Indigenous cultural festivals in Australia, including community festivals (Heydon, 2007), the Garma Festival (Phipps, 2010a, b, 2011; Borthwick, 2011; Pearson, 2011) Laura Aboriginal Dance Festival (Thompson and Connolly, 2006; Henry, 2000a, 2002, 2010; Slater, 2010a; Finch, 2011), The Dreaming Festival (Hanna, 2000; Slater 2007) and the Yalukit Willam Ngargee People Place Gathering in Melbourne (Svoronos, 2010). Case studies then focus on new urban Indigenous festivals attended by the author in Queensland, Australia: the Cairns Indigenous Art Fair (2009, 2010 & 2011) in Cairns; The Torres Strait Islands: A Celebration (2011), and the Reconciliation Beats Concert (2011) both in the capital city of Brisbane. The objectives, sponsorship, cultural program and social or economic outcomes are compared for each urban Indigenous festival. This chapter analyses how these Indigenous festivals contribute to the process of re-territorialisation (Elias-Varotsis, 2006) of Indigenous culture in their original homelands or in new urban locations. The authenticity and sustainability of Indigenous cultural festivals in these new spaces and contexts is also examined.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".