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Record W2062246227 · doi:10.1145/2556288.2556970

Posting for community and culture

2014· article· en· W2062246227 on OpenAlexafffund
Claude Fortin, Carman Neustaedter, Kate Hennessy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPersonalizationComputer scienceAgency (philosophy)Flexibility (engineering)Citizen journalismSpace (punctuation)World Wide WebInternet privacyParticipatory cultureParticipatory designRelevance (law)Public spaceMultimediaHuman–computer interactionSociologyEngineeringPolitical science

Abstract

fetched live from OpenAlex

The next decade is likely to see a shift in digital public displays moving from non-interactive to interactive content. This will likely create a need for digital bulletin boards and for a better understanding of how such displays should be designed to encourage community members to interact with them. Our study addresses this by exploring community bulletin boards as a ubiquitous type of participatory non-digital display "in the wild". Our results highlight how they are used for content of local and contextual relevance, and how cultures of participation, personalization, location, the tangible character of architecture, access, control and flexibility might affect community members' level of engagement with them. Our analysis suggests entry points as design considerations intrinsically linked to the users' sense of agency within a delineated space. Overlaps with related work are identified throughout to provide further validation of previous findings in this area of research.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.129

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 studies0.0000.000
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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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 designTheoretical or conceptual
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

Citations12
Published2014
Admission routes2
Has abstractyes

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