Geographies of Transition: Narrating environmental activism in an age of climate change and ‘Peak Oil’
Bibliographic record
Abstract
The growth of community-based Transition Town initiatives in countries like the UK, USA and Canada is popularly perceived to represent a broad, socially inclusive and grounded approach to tackling environmental problems in place-based communities. In focusing on resilience as a core theme, so-called re-localisation initiatives attempt to adopt consensus based approaches to decision making and to highlight the need for an ‘inner transition’ of the self that encourages closer connections between individuals and nature. In this way, Transition has been framed as a new form of social and environmental movement that is re-casting community and political relations for a low carbon and post ‘Peak oil’ future. Yet despite these emergent philosophies of Transition and the considerable scholarship being generated on the role and success of such initiatives, there is an urgent need to situate and analyse Transition within broader understandings of environmental activism. Using data from a two year research project on ‘Values in Transition’, this paper argues that the praxis and spatial complexity of Transition can be understood more deeply through a narrative lens. In mobilising critical scholarship on environmental activism, the paper calls for a ‘Transition Geographies’ that views re-localisation as a dynamic and complex coalescence of competing narratives that sit between traditional forms of environmental activism and directive initiatives for individual behaviour change. As such, the paper highlights the ways in which this new form of environmental activism is shaping praxis across space, and the implications this has for those advocating re-localisation as a strategy for tackling climate change and resource scarcity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".