The Fires Within Us and the Rivers We Form
Bibliographic record
Abstract
This paper is a creative, poetic and experimental intervention in the form of collective reflections and writings on Anthropology, as the discipline we have experienced and/or been a part of within the University. It is also a reflection on the process of how the authors came together to form the River and Fire Collective. As a collective we have studied, worked and taught in more than 15 universities, and the aspects we point to here are fragments of our experiences and observations of the emotionality of the discipline. These are experiences from different forms of Anthropology from Northern Europe and settler-colonial contexts including Great Turtle Island Canada and Aotearoa New Zealand. In a metaphorical manner we invite the reader to our collective fireside dialogues and reflections, to be inspired, to disagree or agree and to continue a process of transformation. The paper sets out to provocatively question whether Anthropology is salvageable or whether one should ‘let it burn’ (Jobson, 2020). Exploring this question is done by way of discussing decolonial potentialities within the discipline(s), the classroom and exploring fire and water as a radical potential to think through the tensions between abolition and transformation. The reflections engage with concepts of decolonization, whiteness/white innocence, knowledge creation and -sharing, the anthropological self, ethics and accountability and language. The paper emphasizes Anthropology’s embeddedness in colonial narratives, structures and legacies and draws attention to how these colonial, able-bodied realities are being continuously reaffirmed through multiple educational practices and methodologies. It suggests that collectivity in writing, thinking and being is part of a healing process for those of us feeling our way through colonial continuities and prospective potentialities of Anthropology.
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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.035 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 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".