Creating culturally responsive and safe workplaces for the advancement of First Nations people
Bibliographic record
Abstract
Attempting to close the gap with respect to employment of First Nations people is, rightly, a key goal of most Australian businesses. Many companies are developing Reconciliation Action Plans (RAP) or other specific strategies and policies, aimed at engaging, supporting and increasing Indigenous employees within their workforce. However, First Nations people continue to be vastly under-represented in Australia’s workforce; and of those who do obtain work, a much smaller percentage remain in sustainable employment compared to their non-Indigenous colleagues. To achieve meaningful and sustainable change in employment – and therefore the lives – of First Nations people, we must create culturally responsive and safe workplaces. A dedicated Indigenous employment, development and support team at Ventia is doing just that – helping to create an organisational culture that is trauma informed, supports truth-telling conversations, values First Nations people’s unique ways of working, and provides individual and systemic interventions to break down barriers. Using a three-pronged approach – being trauma informed, prioritising personal welfare, and shifting the broader company’s mindset – the TRECCA team is achieving notable results and sustainable advancement for Ventia’s First Nations employees’ and their communities.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| 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".