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Record W2751764714 · doi:10.1057/palcomms.2017.92

Transformation, adaptation and development: relating concepts to practice

2017· article· en· W2751764714 on OpenAlexfundno aff
Roger Few, Daniel Morchain, Dian Spear, Adelina Mensah, Ramkumar Bendapudi

Bibliographic record

VenuePalgrave Communications · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsnot available
FundersInternational Development Research CentreDepartment for International DevelopmentGovernment of the United Kingdom
KeywordsTransformation (genetics)Adaptation (eye)Development (topology)EpistemologyComputer scienceProcess managementPsychologyPhilosophyBusinessMathematicsBiologyNeuroscience

Abstract

fetched live from OpenAlex

Abstract In recent years there has been a growing number of academic reviews discussing the theme of transformation and its association with adaptation to climate change. On the one hand this has stimulated exchange of ideas and perspectives on the parameters of transformation, but it has also given rise to confusion in terms of identifying what constitutes a non-incremental form of adaptation on the ground. What this article aims to do instead is help researchers and practitioners relate different interpretations of transformation to practice by proposing a typological framework for categorising forms of change that focuses on mechanisms and objectives. It then discusses how these categorisations link to the broader conceptions and critiques noted above, with the idea that this will enable those who seek to analyse or plan adaptation to better analyse what types of action are potentially constitutive of transformation. In doing so, it should equally assist in the identification and specification of critical questions that need to be asked of such activity in relation to issues of sustainability and equity.

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)0.023
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.011
Science and technology studies0.0050.128
Scholarly communication0.0230.021
Open science0.0030.011
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.077
GPT teacher head0.341
Teacher spread0.265 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations201
Published2017
Admission routes1
Has abstractyes

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