Understanding Local Responses to Globalisation: The Production of Geographical Scale and Political Identity
Bibliographic record
Abstract
A common perception persists that local responses to globalisation are inherently fundamentalist in nature. The purpose of this essay is to critique two recently published best-selling books that propound this argument. In Lexus and the Olive Tree, Thomas Friedman argues that the globalisation of capitalism is an intrinsically democratic process, which has nonetheless sparked local, fundamentalist reactions. Benjamin Barber argues in Jihad versus McWorld, that democracy, rooted at the scale of the nation-state, is being undermined from above by a globalising consumer culture, and from below by a fundamentalist backlash to globalisation. The Lexus/McWorld versus Olive Tree/Jihad framework therefore implies that local identity-based responses to globalisation are always regressive in nature. This binary division is inadequate because it ignores the many examples of progressive community responses that have also occurred. This essay argues that by adopting a social theory of geographic scale, we can recognise that that nature of local responses to globalisation is a geographically and ideologically open question. The essay concludes by examining three identity-based communities in the US, Canada and Spain to show how they used cooperatives to progressively articulate with the capitalist world economy, while retaining their local identities and attachment to place.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".