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Record W4408803407 · doi:10.29173/cgs177

Gambling in an Australian First Nations Community in the COVID-19 Era

2025· article· en· W4408803407 on OpenAlexvenueaboutno aff
Sarah MacLean, Anastasia Kanjere, Tiffany Griffin, Jai Portelli, Gabriel Caluzzi, Michael Savic, Amy Pennay

Bibliographic record

VenueCritical Gambling Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicPolitical scienceMedicineVirologyOutbreakInternal medicineInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

We report on a collaborative qualitative study to identify gambling expenditure trajectories associated with COVID-19 restrictions on in-venue gambling for people in a regional First Nations Community in Victoria, Australia. Drawing from interviews with 20 First Nations people and seven workers, we use three people’s stories to illustrate experiences associated with: reduced gambling expenditure; little change in gambling expenditure; and increased gambling expenditure. Across each trajectory, many participants took up or increased online gambling during restrictions. The largest proportion returned to pre-COVID-19 gambling expenditure once restrictions eased. Some took the opportunity of a forced break from in-venue gambling to reassess its role in their lives, and a further small proportion spent more money on gambling after the pandemic than prior to it. We highlight the importance of Community in participants’ capacities to manage gambling during this period. Participants described the presence of Community members at in-venue gambling as limiting their spending, something that became unavailable when gambling online at home during lockdowns. Willpower was identified as most participants’ preferred means of managing gambling. This worked for some, but others noted that the ubiquity of online gambling products and ongoing effects of trauma and disadvantage stymied their efforts. As some participants insisted, the gambling industry and governments that are its beneficiaries perpetuate colonization by extracting money from First Nations peoples, with gambling harm attributed to Indigeneity rather than poverty resulting from colonization and dispossession. Thus, First Nations Communities and individuals are held responsible for problems that are largely not of their making.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0150.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.222
GPT teacher head0.513
Teacher spread0.291 · 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 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
Published2025
Admission routes2
Has abstractyes

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