Criminologists, duct tape, and Indigenous peoples: quantifying the use of silencing research methods
Bibliographic record
Abstract
A recent quantitative evaluation of mainstream criminological research found that there is a dearth of research on “Indigenous peoples in the criminal justice context” conducted in Australia, Canada, New Zealand, and the United States and published in elite criminology journals while these nations continue to incarcerate Indigenous peoples at markedly disproportionate rates. Although the silence prohibits public attention to this social issue, counter-colonial critics have mostly focused on criminologists who deliberately marginalize Indigenous peoples through use of inappropriate research methods. This study is a first attempt to quantify the use of “silencing research methods” in contemporary mainstream criminology. It involves a comprehensive review of research published in elite criminology journals over the past decade (2001–2010). The findings reveal that although mainstream criminologists generally prefer non-silencing research tools, they primarily employ silencing research methods when studying Indigenous peoples. Also, studies that focus on Native American peoples use silencing research tools more often than studies on other disproportionately incarcerated social groups, i.e., African and Hispanic Americans. The study concludes that by using “silencing research methods,” elite mainstream criminology has contributed to the marginalization of Indigenous peoples to varying degrees in all four countries over the past decade.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".