IndigiComms: using decolonization, power studies and Indigenous methods to inform postmodern communications practice & scholarship
Bibliographic record
Abstract
At a Blackfoot Sundance in 2015, I prayed for Creator to help me fit together the oppositions in my life — such as Indigenous studies and public relations/communications scholarship, and my mixed Indigenous and non-Indigenous ancestry. I believe that prayer lead me here — to this paper. In it, I grappled with the question on how the study in Indigenous methods, decolonization studies and media histories could inform the future of a postmodern communications scholarship and practice, while at the same time positing that these will be the very tools needed for the future of ethical public relations scholarship and practice. The primary source of data for this work comes from an auto ethnographical account of confronting research works within deeply entrenched colonial institutions, and reflects some key markers on my journey as I read and researched works within the disciplines of Indigenous studies, Indigenous Methodologies, media histories and postmodern thought in communication studies. My research spanned across various disciplines such as Francis’s (1992) exploration of the history behind mainstream Indigenous imaging, which referenced John Dryden’s 1670 play The Conquest of Granada as one of the first places the image of the ‘noble savage’ appeared (p. 7). And I ended my research with post-modern calls to public relations practitioners from Holtzhausen (2002) who claimed that reflexivity could help prevent the formation of metanarratives or dominant discourses in public relations. Further, she also cautioned practitioners to critique their own actions using postmodern theory (pp. 256, 259). I am not accomplished expert in these fields. I am a scholar. And ethical considerations remind me that this work, and the use of a made-up term like “IndigiComms,” is simply a quiet form of activism — of placing me in the centre of my work using a small ‘i’. I did not need to figure out how to do put these things together, I just needed to find the courage to continue to do what I’ve been doing this whole time — using my voice and my stories. My hopes are that this story can help inform the future of Indigenous communications and public relations scholarship: a discipline lacking in Indigenous Methodologies for research, scholarship and practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.011 | 0.047 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".