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Record W1890385970 · doi:10.17169/fqs-15.2.2040

Mapping the Complexities of Online Dialogue: An Analytical Modeling Technique

2013· article· en· W1890385970 on OpenAlexaff
Robert Newell, Ann Dale

Bibliographic record

VenueForum: Qualitative Social Research (Freie Universität Berlin) · 2013
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsComputer scienceData science

Abstract

fetched live from OpenAlex

The e-Dialogue platform was developed in 2001 to explore the potential of using the Internet for engaging diverse groups of people and multiple perspectives in substantive dialogue on sustainability. The system is online, text-based, and serves as a transdisciplinary space for bringing together researchers, practitioners, policy-makers and community leaders. The Newell-Dale Conversation Modeling Technique (NDCMT) was designed for in-depth analysis of e-Dialogue conversations and uses empirical methodology to minimize observer bias during analysis of a conversation transcript. NDCMT elucidates emergent ideas, identifies connections between ideas and themes, and provides a coherent synthesis and deeper understanding of the underlying patterns of online conversations. Continual application and improvement of NDCMT can lead to powerful methodologies for empirically analyzing digital discourse and better capture of innovations produced through such discourse. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs140221

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.003
Open science0.0020.001
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 head0.350
GPT teacher head0.467
Teacher spread0.117 · 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.

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

Citations2
Published2013
Admission routes1
Has abstractyes

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