First Nations women's experiences of technology-facilitated abuse in family violence settings: help-seeking and support
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This research explores First Nations women's experiences with technology-facilitated abuse (TFA) within family violence settings; help seeking and supports. This is an all-Indigenous project that situates First Nations women centrally.The scarcity of research currently available examining this continents First Nations women's experiences with family violence and TFA is unmistakable. Within the broader context of family violence, TFA is becoming increasingly problematic for many women. First Nations women already encounter a heightened risk of violence due to colonisation and systemic inequalities and are particularly at risk. This form of abuse weaponises various modes of technology such as social media platforms, mobile phones and other devices to stalk, threaten, monitor and control. The convergence or intersection of gender, Indigeneity, digital literacy and access results in First Nations women experiencing intensification of its occurrence, impact and a reduction in help-seeking pathway options.In a broader sense, this research is intended to be spread across two phases. Phase one (Masters) this thesis, focuses on exploring First Nations women’s experiences and knowledge of TFA in the context of family violence. Phase two (PhD) research project will be heavily informed and shaped by the findings of this Master’s thesis. Throughout, priority is placed on Indigenous research methodologies and methods including yarning (Bessarab & Ng'andu, 2010), two-way learning (Bell et al., 2011) and the cultural practice of weaving. For both phases, I aim to amplify the voices of First Nations women victim-survivors of TFA, with the firm belief that First Nations women know what they need to support them - they just need to be heard (AHRC, 2020).
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it