MétaCan
Menu
Back to cohort

Social Computing and Social Software

2009· book-chapter· en· W2498128241 on OpenAlexaff
Ben Kei Daniel

Bibliographic record

VenueIGI Global eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWorld Wide WebWeb engineeringWeb developmentWeb standardsComputer scienceWeb modelingWeb intelligenceWeb Accessibility InitiativeWeb 2.0Social Semantic WebHypertextWeb navigationSocial webSocial softwareSocial mediaThe InternetData scienceWeb service

Abstract

fetched live from OpenAlex

The World Wide Web is one of the most profound technological inventions of our time and is the core to the development of social computing. The initial purpose of the Web was to use networked hypertext system to facilitate communication among its scientists and researchers, who were located in several countries. With the invention of the Web came three important goals. The first was aimed at ensuring the availability of different technologies to improve communication and engagement. The second goal was to make the Web an interactive medium that can engage individuals as well as enrich communities’ activities. The third goal was for the Web to create a more intelligent Web, in addition to being a space browseable by humans. The Web was developed to be rich in data, promoting community engagement, and encouraging mass participation and information sharing. This Chapter describes general trends linked to the development of the World Wide Web and discusses its related technologies within the milieu of virtual communities. The goal is to provide the reader with a quick, concise and easy way to understand the development of the Web and its related terminologies. The Chapter does not account for a more comprehensive analysis of historical trends associated with the development of the Web; neither does it go into a more detailed technical discussion of Web technologies. Nonetheless, it is anticipated that the materials presented in the Chapter are sufficient to provide the reader with a better understanding of the past, present and future accounts of the Web and its core related technologies.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.841
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.026
GPT teacher head0.294
Teacher spread0.268 · 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
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueIGI Global eBooksSame topicSocial Capital and NetworksFrench-language works237,207