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Record W4232506822 · doi:10.4018/978-1-60960-869-9

Virtual Community Building and the Information Society

2011· preprint· en· W4232506822 on OpenAlexaff

Bibliographic record

VenueIGI Global eBooks · 2011
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsYork University
Fundersnot available
KeywordsArchitectural engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

The research and development on spoken dialog systems embraces technical, user-centered and business-related perspectives. It brings together stakeholders belonging to distinct job families, therefore prone to different traditions and practices. When assessing their contributions, as well as the final solution, they conduct very nomadic evaluation protocols. As a result, the field is eager to set up norms for evaluation. Contributions abound in this way. However, despite standardization exercises, we believe that the absence of common conceptual foundations and dedicated knowledge creation spaces frustrate the effort of convergence. The chapter therefore presents an application framework meant to rationalize the design of evaluation protocols inside and across project teams. This Multi Point of VieW Evaluation Refine Studio (MPOWERS) enforces common models for the design of evaluation protocols. It aims at facilitating, on the one hand, the individual evaluator-users task and, on the second hand, the emergence of (first virtual, then maybe real) communities of practice and multidisciplinary communities of interest. It illustrates how implementing shared knowledge frameworks and vocabulary for non-ambiguous asynchronous discussions can support the emergence of such virtual communities.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score0.703

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.003
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 head0.029
GPT teacher head0.239
Teacher spread0.210 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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