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Record W3093068076 · doi:10.1002/2688-8319.12028

Navigating spaces between conservation research and practice: Are we making progress?

2020· article· en· W3093068076 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

VenueEcological Solutions and Evidence · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsAction (physics)Engineering ethicsPublic relationsPolitical scienceComputer scienceManagement scienceEngineering

Abstract

fetched live from OpenAlex

Abstract 1. Despite aspirations for conservation impact, mismatches between research and implementation have limited progress towards this goal. There is, therefore, an urgent need to identify how we can more effectively navigate the spaces between research and practice. 2. In 2014, we ran a workshop with conservation researchers and practitioners to identify mismatches between research and implementation that needed to be overcome to deliver evidence‐informed conservation action. Five mismatches were highlighted: spatial, temporal, priority, communication, and institutional. 3. Since 2014, thinking around the ‘research–implementation gap’ has progressed. The term ‘gap’ has been replaced by language around the dynamic ‘spaces’ between research and action, representing a shift in thinking around what it takes to better align research and practice. 4. In 2019, we ran a follow‐up workshop reflecting on this shift, whether the five mismatches identified in the 2014 workshop were still present in conservation, and whether progress had been made to overcome these mismatches during the past 5 years. We found that while there has been progress, we still have some way to go across all dimensions. 5. Here, we report on the outcomes of the 2019 workshop, reflect on what has changed over the past 5 years, and offer 10 recommendations for strengthening the alignment of conservation research and practice.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.614
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.605
GPT teacher head0.468
Teacher spread0.137 · 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