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Record W2070846952 · doi:10.1109/hicss.2010.317

Research 2.0: A Framework for Qualitative and Quantitative Research in Web 2.0 Environments

2010· article· en· W2070846952 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
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceDomain (mathematical analysis)Web applicationData scienceKey (lock)Web intelligenceQualitative researchWeb modelingWeb 2.0World Wide WebFace (sociological concept)Knowledge managementManagement scienceThe InternetEngineeringSociology

Abstract

fetched live from OpenAlex

The paper explores the potential of the Web 2.0 environment for conducting both qualitative and quantitative research. The paper analyzes the emerging Research 2.0 domain using the theoretical framework of Web 2.0 core principles (e.g., web as a platform, harnessing collective intelligence, etc.). These principles, first proposed by Tim O'Reilly, provide a useful lens through which researchers can examine the potential for Web 2.0 technologies in shaping the next generation of research methodologies. To this end, the paper examines how these principles would apply to the research domain, how traditional methodologies used in qualitative and quantitative research can be applied within a Web 2.0 environment, and the challenges and issues that researchers may face in a Research 2.0 domain. The paper identifies key research issues that need to be explored to fully realize the potential of Web 2.0 technologies in conducting qualitative and quantitative 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.

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)0.069
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0690.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.572
GPT teacher head0.679
Teacher spread0.107 · 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

Citations21
Published2010
Admission routes1
Has abstractyes

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