The best of intentions: mainstreaming, the not-for-profit sector and Indigeneous Australians
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 study investigates interconnections between government approaches to policy in Indigenous affairs – characterised by mainstreaming of services for Indigenous Australians – and the ways in which the not-for-profit sector (NFP) has responded. In terms of both policy and practice it offers a window on the intercultural and interpersonal challenges for organisations and individuals working in the cross-cultural spaces evolving between mainstream (white) organisations and Indigenous Australians. The thesis offers a detailed case study of Australian Red Cross – one of Australia’s oldest and most prestigious humanitarian organisations. In 2007, Red Cross commenced new programs and services for Indigenous Australians as part of its mission “to help the most vulnerable”. Drawing on Nakata’s concept of the “cultural interface” and field-based research across Australian Red Cross, the thesis explores the interfaces between Indigenous staff, the organisation, and Indigenous communities in the early stages of this venture during the period 2010-2012. The thesis also reviews in detail the experience and challenges of adapting and introducing a Canadian family/community safety program to Australia as an Indigenous community development program. As NFPs move into domains that were previously mainly Indigenous and with increased co-dependence between the NFP sector and government in providing Indigenous programs and services, the thesis offers a timely account of lessons, risks and challenges for all involved. In conclusion, the thesis questions whether the current policy direction and its resulting collaboration between governments and the mainstream NFP sector have secured the outcomes intended.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 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 it