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Record W4281923114 · doi:10.5194/agile-giss-3-7-2022

Six GIScience Ideas That Must Die

2022· article· en· W4281923114 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

VenueAGILE GIScience Series · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsMcGill University
FundersFundação para a Ciência e a Tecnologia
KeywordsSloganEpistemologySociologyGeoinformaticsEngineering ethicsData scienceComputer sciencePolitical sciencePhilosophyEngineeringLawGeography

Abstract

fetched live from OpenAlex

Abstract. In 2015, John Brockman edited a volume of chapters contributed by leading thinkers from various domains discussing common scientific ideas hindering further scientific progress. While starting with the provocative slogan of This Idea Must Die, the book’s chapters and their authors (for most parts) do not argue that those existing – often foundational scientific theories from various domains – are false, but instead that their widespread, and often unquestioned, utilization has started to hinder the evolution of new theories. Through this work, we would like to foster a similar discussion in our community, by suggesting six ideas in GIScience/geoinformatics that may benefit from retiring to make room for new perspectives. Our suggestions are somewhat controversial, and readers are encouraged to keep an open mind.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.695
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0090.003
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.280
Teacher spread0.251 · 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