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Guerrilla geography: describing and defending place for a living (or the renaissance of 100–mile geographers)

2014· book-chapter· en· W2496583646 on OpenAlexaboutno aff
Briony Penn

Bibliographic record

VenueManchester University Press eBooks · 2014
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCitizen journalismGeographySociologyPolitical science

Abstract

fetched live from OpenAlex

The abandonment of regional geography in the mid 20th century through pressures of globalization, urbanization and corporatization lost two generations of local knowledge and engagement. Studying place, finding the genius of loci, helping communities to articulate the uniqueness and relevance of place has been left to poets, activists and guerrilla geographers. The chapter looks at the role of guerrilla geography in the renaissance of place, community mapping and naming of place, and ultimately the protection and restoration of place through the word and illustrations of one practitioner from Canada’s rarest ecosystem—the Garry oak meadows overlooking the Salish Sea. Up until 1991, this drought‐adapted ecosystem, now the focus of research on ecosystem resilience in climate change, had no name, no map, no cultural identity beyond Little England, no recognition from academia and no protection. With the return to localism and demand for regional solutions, what is the role for young guerrilla geographers in their respective places across Canada? This discussion will chart a course of meaningful work as we pick up the lost stories of place and weave them with the new. It suggests ways for the academic community to support, educate and legitimize the next generation of guerrilla geographers.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.287
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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