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Record W3179007895 · doi:10.5209/arab.72801

The Role of Local Content in Wikipedia: A Study on Reader and Editor Engagement

2021· article· en· W3179007895 on OpenAlexaboutno aff
Marc Miquel-Ribé, David Laniado, Andreas Kaltenbrunner

Bibliographic record

VenueÁrea Abierta · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
FundersIntesa Sanpaolo Innovation Center
KeywordsRelevance (law)Context (archaeology)Content (measure theory)PoliticsQuarter (Canadian coin)World Wide WebMedia studiesSociologyComputer scienceHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

About a quarter of each Wikipedia language edition is dedicated to representing “local content”, i.e. the corresponding cultural context (geographical places, historical events, political figures, among others). To investigate the relevance of such content for users and communities, we present an analysis of reader and editor engagement in terms of pageviews and edits. The results, consistent across 15 diverse language editions, show that these articles are more engaging for readers, and especially for editors. The highest proportion of edits on cultural context content is generated by anonymous users, and also administrators engage proportionally more than plain registered editors. In fact, looking at the first week of activity of every editor in the community, administrators already engage proportionally more than other editors in content representing their cultural context. These findings indicate the relevance of this kind of content both for fulfilling readers' informational needs and stimulating the dynamics of the editing community.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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