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Record W4410278078 · doi:10.1016/j.envsoft.2025.106519

Applying user-centred design to climate and environmental tools

2025· article· en· W4410278078 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Modelling & Software · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
FundersWageningen University and ResearchAgricultural Research ServiceConsortium of International Agricultural Research CentersVlaamse OverheidForeign, Commonwealth and Development OfficeDepartment for International DevelopmentAustralian GovernmentInternational Development Research CentreVlaamse regeringUniversity of Nebraska-LincolnBill and Melinda Gates FoundationU.S. Department of Agriculture
KeywordsComputer scienceEnvironmental resource managementHuman–computer interactionEnvironmental science

Abstract

fetched live from OpenAlex

The number of web portals and online tools to support or inform decision-making on environmental and climate issues has grown steadily in recent decades. This paper explores the benefits and challenges of applying user-centred design (UCD) in environmental tool development, drawing on three case studies at the science-policy interface. We examine the roles and perspectives of scientists, funders, software developers, and end-users, highlighting how their often conflicting objectives can lead to a lack of focus. Active management is essential to align tool development with user needs. To increase the credibility and usefulness of environmental tools, we argue for stronger adoption of UCD, greater attention to post-creation tool use, and better integration of tool development into broader project lifecycles. Finally, we recommend building on or improving existing tools and platforms rather than developing new ones for each project, fostering greater continuity, efficiency, and long-term impact in the science-policy interface.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.030
GPT teacher head0.205
Teacher spread0.175 · 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