Bibliographic record
Abstract
One of the distinctive features of settler-colonial jurisdictions – namely New Zealand, Australia, Canada and the United States – is the significant over-representation of Indigenous peoples in all facets of the criminal justice system. Research consistently shows that Indigenous peoples are over-represented in arrest, conviction and imprisonment statistics, as well as rates of victimization, especially for crimes involving sexual and intimate partner violence. The lived experiences of Indigenous peoples have long been associated with rurality, meaning that community structures are located in geographical spaces we understand today to be ‘rural’. Appending Indigenous lived experience with rurality has become associated with socio-economic deprivation that manifests in a range of poor social outcomes, including low educational attainment, poor health outcomes, drug and alcohol dependency, high rates of child abuse and/or negative engagement with childcare and protection services, intimate partner and other forms of violence (see both Guggisburg, 2019 and McCausland and Vivian, 2010). It is no surprise, then, that connections between the concept of rurality and Indigenous peoples’ experiences of offending and victimization has long been established in criminology. Furthermore, it is becoming a key focus of research and analysis of the Indigenous lived experience within the developing sub-discipline of rural criminology (see Jones et al, 2016). However, focusing investigation and analysis of Indigenous peoples’ experiences of crime and victimization within the geographical and conceptual space of ‘rurality’ is problematized by the fact that the demographic reality of Indigenous lived experience is not the same for all Indigenes. For example, in the Canadian context, only 26 per cent live ‘on reserve’, meaning that 74 per cent of Canadians who self-identify as Indigenous live ‘off reserve’.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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.
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".