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Engaging With the Participatory Geoweb

2017· book-chapter· en· W2592436657 on OpenAlex
Jon Corbett, Logan Cochrane

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

VenueAdvances in geospatial technologies book series · 2017
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVolunteered geographic informationCitizen journalismExperiential learningKnowledge managementIncentiveEmpowermentParticipatory GISPower (physics)Public relationsPolitical scienceSociologyData scienceComputer scienceWorld Wide WebPedagogy

Abstract

fetched live from OpenAlex

Maps were historically used as tools of the elite to maintain and expand power and control. The development of participatory mapmaking and the geoweb have opened new avenues for broader citizen engagement and therefore challenge traditional power dynamics. This chapter analyzes three examples and presents experiential learning around participatory processes and VGI contributions. Specifically we explore who is contributing their information, what are their motivations and incentives, in what ways do users interact with available technologies, and how is this contributing to change? We conclude by discussing the roles of motivations, the type of contribution, organizational capacity and leadership, and objectives. In comparing and contrasting these case studies we examine the individual and organizational dynamics of engagement, and how this can better inform the discourse about VGI.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.006
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.288
Teacher spread0.264 · 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