Between the Camp and the Makerspace: Commoning Practices, Temporal Autonomy and Care
Bibliographic record
Abstract
The paper explores the chronopolitics of place-making in the refugee makerspace Habibi-Works and the neighbouring Katsikas refugee camp in Ioannina, in Northern Greece. Camps are created to be ephemeral and this ephemerality is reflected in their materiality and conditions the possibilities available to those that inhabit them. Camp temporalities work by way of destabilising the residents' sense of self in the present, severing their connections with the past and limiting their future aspirations. In sheer antithesis to the camp, the makerspace disrupts these (temporal) dynamics: it enables the camp residents to manage time as a common resource (commoning), creating autonomous communities of collective care. Through mundane encounters and practices, the makerspace plays an instrumental role in enacting the residents' autonomy by facilitating access to digital technologies, low-tech manufacturing tools, and skills to reproduce a sense of lost normality. We adopt an ethnographic approach to engage with the makerspace and the camp as well as the various people involved (migrants, volunteers, makers) and understand how migrants narrate their past, negotiate their present and imagine their futures in the context of everyday life. Building on the concepts of peer production, temporal autonomy and radical care, we argue that Habibi-Works opens up a new socio-political space between the camp, the makerspace and the world.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.044 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".