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Record W7075712542

Land Grabbing and Global Governance

2013· other· en· W7075712542 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMax Planck Digital Library · 2013
Typeother
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsLand grabbingGlobal governanceContext (archaeology)Corporate governancePower (physics)GlobalizationGlobal cityInternational development
DOInot available

Abstract

fetched live from OpenAlex

Land grabbing per se is not a new phenomenon, given its historical precedents in the eras of imperialism. However, the character, scale, pace, orientation and key drivers of the recent wave of land grabs is a distinct historical event closely tied to the changing dynamics of the global agri-food, feed and fuel complex. Land grabbing is facilitated by ever greater flows of capital, goods, and ideas across borders, and these flows occur through axes of power that are far more polycentric than the North-South imperialist tradition. Land grabs occur in the context of changes in the character of the global food regime, formerly anchored by North Atlantic empires; the integrated food-energy complex seems to be headed towards multiple centres of power, especially with the rise of the BRICS and the proliferation of middle income countries participating in many of the land transactions. Land Grabbing and Global Governance offers insights from leading scholars and experts on contemporary land grabs. This volume examines land grabs in direct relation to a global economy undergoing profound change and the role of new configurations of actors and power in governance institutions and practices.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.381
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.002
GPT teacher head0.160
Teacher spread0.158 · 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