Boundary spanners: An Australian First Nations perspective
Bibliographic record
Abstract
Abstract A boundary spanner is a person who breaks down the barriers or ‘boundaries’ between specific groups of society. To do this, they use their innate qualities and skills developed through experience to conceptualise a method which facilitates meaningful relationships between the two groups. As Indigenous knowledges in Australia and the world are increasingly elevated as meaningful and valid by the Western academy, and our planet faces global environmental challenges, it has never been more important to understand the role and characteristics of people who are boundary spanners—those that bridge the gap between Indigenous peoples and the Western academy. There are many characteristics exhibited by effective boundary spanners. Many, if not all, of these characteristics are innate, strengthened through their experiences with Indigenous peoples and grounded in ethics and respect for culture and customs, and very importantly, integrity and honesty. Being an effective boundary spanner, however, comes with challenges. These challenges include issues of trust, perception, respect, identity, burn out, time management, competing timeframes and the capacity to create pathways and repair relationships. The boundary spanner must find solutions for these challenges to build positive relationships between themselves, the academy and the Indigenous community. This is needed to collectively find solutions to environmental challenges. This perspective piece sets out to highlight the importance of boundary spanners, the characteristics they have and the challenges they face in the ‘in between’ place they occupy between the Western academy and Indigenous communities. The aim of this perspective piece was to help Western academy to identify and understand the value of boundary spanners and develop a language to move forward in a meaningful dialogue about Indigenous knowledges and peoples at a time when the need for boundary spanners is substantial in Australia and globally if we are to sustain Land, Sea and Sky Country. Read the free Plain Language Summary for this article on the Journal blog.
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 | 0.000 | 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 | 0.009 | 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".