“Harmful to the commonality”: the Luddites, the distributional effects of systems change and the challenge of building a just society
Bibliographic record
Abstract
Purpose When complex social-ecological systems collapse and transform, the possible outcomes of this transformation are not set in stone. This paper aims to explore the role of social imagination in determining possible futures for a reformed system. The authors use a historical study of the Luddite response to the Industrial Revolution centred in the UK in the early-19th century to explore the concepts of path dependency, agency and the distributional impacts of systems change. Design/methodology/approach In this historical study, the authors used the Luddites’ own words and those of their supporters, captured in archival sources (n = 43 unique Luddite statements), to develop hypotheses around the effects on political, social and judicial consequences of a significant systems transformation. The authors then scaffolded these statements using the heuristics of panarchy and basins of attraction to conceptualize this contentious moment of British history. Findings Rather than a strict cautionary tale, the Luddites’ story illustrates the importance of environmental fit and selection pressures as the skilled workers sought to push the English system to a different basin of attraction. It warns us about the difficulty of a just transition in contentious economic and political conditions. Social implications The Luddites’ story is a cautionary tale for those interested in a just transition, or bottom-up systems transformation generally as the deep basins of attraction that prefer either the status quo or alternate, elite-favouring arrangements can be challenging to shift independent of shocks. While backward looking, the authors intend these discussions to contribute to current debates on the role(s) of social innovation in social and economic policy within increasingly charged or polarized political contexts. Originality/value Social innovation itself is often predicated on the need for just transitions of complex adaptive systems (Westley et al., 2013), and the Luddite movement offers us the opportunity to study the distribution effects of a transformative systems change – the Industrial Revolution – and explore two fundamental questions that underpin much social innovation scholarship: how do we build a just future in the face of complexity and what are likely forms those conversations could take, based on historical examples?
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.076 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".