MétaCan
Menu
Back to cohort
Record W2587850015 · doi:10.1145/3022198.3024941

Motivations for Participating in Online Initiatives

2017· article· en· W2587850015 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCrowdsourcingScholarshipPeer productionPublic relationsWork (physics)Citizen scienceKnowledge managementOnline participationSociologyPolitical scienceComputer scienceWorld Wide WebThe InternetEngineering

Abstract

fetched live from OpenAlex

Online initiatives, a term that describes goal-oriented systems such as crowdsourcing, peer production, and online communities, are increasingly popular ways to source work from and harness the skills of distributed populations. The explosion of online initiatives in recent years has inspired scholarship examining why people contribute to these initiatives. While there is an abundance of case studies on motivation, there is a dearth of research that explores motivation between initiative types. Through case studies of two online initiatives, my dissertation research explores relationships between initiative structure, engagement, and participant role on motivation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.105
GPT teacher head0.385
Teacher spread0.279 · 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

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicOpen Source Software InnovationsFrench-language works237,207