Introduction: Restructuring Regions: Doreen Massey on Uneven Geographical Development
Bibliographic record
Abstract
Like several of human geography’s other luminaries of the past half-century, Doreen Massey had a deep, career-long interest in the question of uneven geographical development. It was always with her, animating her politics as much as her research practice, from the early 1970s through to the early 2010s. Embracing the challenge of understanding uneven geographical development as a concrete abstraction, Massey approached it by way of iteration between theory and particular empirical and political contexts: it was first and foremost uneven development in Britain that exercised her, and her ability to show how her particular conceptualisation of uneven development – which she coined “spatial divisions of labour” – helped explain the consequential particularities of the British case has inspired a generation of economic geographers. Developed in and “of” Britain, the idea of spatial divisions of labour nonetheless could be (and has been) mobilized to illuminate actually-existing economic-geographic realities much further afield. And at its core is the region. Uneven geographical development is, for Massey, a complex, continuous and multi-layered dynamic of regional restructuring . This dynamic is the common thread running through the six chapters in Part 1 of this book. As ever with original thinkers such as Massey, the stimulus to innovative theorization was a realization that existing approaches to understanding the object of interest – in her case, pronounced intra-national spatial variegation in economic processes and outcomes – were simply not up to the task. Most obviously this was true, in Massey’s view, of the prevailing economic orthodoxy, neoclassicism, the paradigmatic dominance of which was to be seriously challenged by the modestly titled “Towards a critique of industrial location theory” (Chapter 2). But, significantly, she also thought it was true of the array of heterodox economic approaches that were in circulation during that period – the 1970s – when she began to explore uneven development and to develop her own unique approach to its conceptualization, a process that began in an appropriately grounded way in “Regionalism: some current issues” (Chapter 5; see also Chapter 14). As Massey saw it, the principal cause of the inadequacy of these various approaches was their weak or simply flawed conceptualization of space. If, as she would later famously insist, geography matters, then neither neoclassicism nor existing heterodoxies adequately showed how or why.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".