Identity, Community, and Technology: Reflections on the Facebook Group Inuit Hunting Stories of the Day
Bibliographic record
Abstract
In this article I reflect on a particular Inuit use of the social networking site Facebook: the group called Inuit Hunting Stories of the Day. I focus on two main issues. First, I discuss the logic behind current technologies as conceptualized by Albert Borgmann (e.g., 1984), who states that rather than being neutral tools, modern devices foster a particular “taking-up” with the world that leads to disengagement from community and meaningful practices. Arguing against this view, I discuss how Inuit Hunting Stories of the Day is an example of how the internet and Facebook are appropriated and provide meaningful engagement. Second, I follow anthropologist Claudio Aporta’s (2013) notion of ecology of technology and argue that the relationship between technology and Inuit has to be understood within an ecological framework that encompasses the broader context of political, economic, and social change, which are intertwined with the use, appropriation, adoption, and adaptation of technology. Drawing from the ecology of technology perspective, it is my central argument that technology and computer-mediated communication bring proximity to cultural practices, activities, and the land rather than provoking distance and alienation from reality, as commonly expressed in dystopian notions.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.055 | 0.040 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.005 | 0.010 |
| 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".