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Resources and Development

2017· other· en· W2783445508 on OpenAlexaff
Roger Hayter, Jerry Patchell

Bibliographic record

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDiversification (marketing strategy)Resource (disambiguation)Natural resourcePerspective (graphical)Corporate governanceExploitation of natural resourcesBusinessEnvironmental resource managementEconomic geographyGeographyPolitical scienceEconomicsComputer scienceMarketing

Abstract

fetched live from OpenAlex

The relationships between natural resources and development are profoundly important, but contingent and contradictory. This entry's objectives are to summarize the problematical implications of resource exploitation for economic diversification, and to discuss the implications of resource conflicts for development, particularly with respect to resource peripheries. The dilemmas of resource‐based development are first contextualized from the perspective of resource governance, multifunctionality, and cycles. The factors encouraging and inhibiting the industrial diversification of export‐based resource peripheries are then outlined. Finally, the transformation of resource–development relationships is revealed by reference to resource conflicts and the growing importance of environment and cultural factors. Geography has an important role to play in understanding resource conflicts and their resolution.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.053
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.006
Scholarly communication0.0100.004
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0530.008

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 head0.006
GPT teacher head0.206
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations18
Published2017
Admission routes1
Has abstractyes

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