Futures of industrial work? Economic restructuring and the ambivalent realities of technological change
Bibliographic record
Abstract
The ‘future of work’ in manufacturing or similarly positioned ‘productive’ sectors is an increasing public and academic concern. Debate tends to polarize between anxious and dystopic accounts that explore the threat of technological change to existing industries and celebratory, optimistic accounts that focus on the ambitious promises of possible futures. In response, a critical labour studies scholarship has argued that these narratives tend to be overly determined by conversations about technology and less focused on how technological transformation has historically and will continue to exacerbate, reinscribe, or reshape existing exclusions within labour markets and workplaces. These optimistic narratives also fail to address the non-technological drivers of the global restructuring of work and employment, in particular the way the current realities of work are rooted in (neo)colonial, racialized, and gendered histories and presents of exploitation, resource extraction, and social reproduction. Drawing on five empirical contributions from a variety of industrial contexts across the Global South and North, this special issue deepens our understanding of how ‘future of work’ discourses and practices, including efforts (and desires) to automate and innovate, impact and coexist with industries and labour relations that have hitherto been slow to automate, remain un-automated, or are resistant to technological change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".