Collaborative repair as dealienation: an exploration of degrowth technology practice
Bibliographic record
Abstract
The degrowth hypothesis could be summarised by the following: even if limitless growth were biophysically possible—which it is almost certainly not—it would not be desirable. The degrowth project bills itself as more than just critique: it is “a normative concept with analytical and practical applications” (Kallis et al 2018). Yet while scholarship has meaningfully engaged with ecological economics and political ecology to interrogate the metabolic imbalances and distributional asymmetries of growth-centric society, empirical investigation of alternative “living degrowth” are rare (Brossman and Islar 2020). Degrowth research focusing on questions of technological normativity, or “technology practice” (Drengson 1995) are few and mostly limited to work adopting largely quantitative, or metabolic, approaches to technology, for instance in the ‘low-tech’ movement. These predominantly biophysical framings are clearly necessary in apprehending, and acting upon, the impossibility of endless growth and commodity innovation/production. They are however, less adequate in accounting for the undesirability of endless growth and material accelerations, and in indicating new, more desirable pathways for technology practice moving forward. \nThe present empirical study consists in first-person observation and interviews carried out in a Montreal amateur repair community in 2021-2022. The phenomenon of collaborative repair, or Repair Cafés, is a practice geared to the downscaling of material throughput through the collectivisation of tools, space and repair knowledge. Through observation and analysis, a cluster of questions was asked: how could we begin to think about degrowth technology practice? What would it look like? Can the features of collaborative repair offer us hints? Drawing on recent scholarly efforts to revive ‘alienation’ as a valid theme for social inquiry, and in addressing the noted need for degrowth to think more seriously about “dealienation” (Brownhill et al 2012), the present study looks at collaborative repair as a testing site for the suitability of these concepts, and for their potential application in a proposed degrowth research mandate focused on technology practice. This study is founded on a methodological conviction that when one engages in practice, one not only does something, one also understands that one is doing something, inevitably investing the action with meaning (Jaeggi 2018). From this point of view, and beyond metabolic and redistributive ends, collaborative repair effects a rehabilitation of meaningful subject-subject, subject-time and subject-object relations—relations typically characterised by alienation in industrial commodity economies. The present study also recommends that degrowth think seriously about “resonance” (Rosa 2019) as a more useful and coherent alternative to ‘autonomy’ when conceptualising alienation’s ‘other’. Such a framing appears critical for both elaborating a degrowth critique of technology and enriching discussions of how degrowth normativity bears on 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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".