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Record W2064831814 · doi:10.1002/meet.1450430136

Life after WSIS: Lessons learnt and implications for the information professions

2006· article· en· W2064831814 on OpenAlexaff
Leslie Chan, Sheri Weber, Robert Guerra, Michel J. Menou, Nadia Caidi, John N. Gathegi

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Society and Technology Trends
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSummitMarketing buzzPolitical sciencePublic relationsInformation societySession (web analytics)AllianceBusinessComputer scienceWorld Wide WebGeography

Abstract

fetched live from OpenAlex

In November 2005, the World Summit on the Information Society (WSIS) “concluded” with the second phase meeting in Tunis. The goal of WSIS was to garner global attention, devise effective policies, and identify promising applications and business models for capturing the promise of ICTs for all. The International Telecommunication Union paved the way, along with a vast number of players and stakeholders, for the two-phase summit (the first phase was held in Geneva in 2003). Countless numbers of preparatory meetings and submissions from a diverse set of stakeholders have gone into the making of the WSIS. The outcomes of the two WSIS phases were more limited than one would have expected or hoped for. Nevertheless a number of important developments are in the works, such as the Internet Governance Forum, the Digital Equity Fund, the global alliance on IT4Dev to name a few. Thus increased attention to and involvement in these developments are still, if not more, necessary. The aim of this session is to gather leading individuals who have been actively engaged in the WSIS discussions and can shed light on the lessons learnt from the Summit, as well as what the implications might be for the information science community. Indeed, the Summit did not really engender the expected buzz within the information science community: why is that so? This session aims to generate a broad discussion about the opportunities and challenges afforded by having a World Summit on information-related issues. What has been achieved or not at the two rounds of WSIS The major issues addressed and the issues of contention The participation of and implications for information professionals. Fostering a debate on the WSIS issue is essential in order to assess why WSIS was not more successful, but even more important to explore what can be done with what was achieved, and where the future of information societies seem to lie. WSIS needs not be “dead” and gone already. Rather it seems to be more essential than ever to reflect on the lessons we can learn from it. The aim of this session is to enable discussion around WSIS and the after-WSIS landscape to take place within the ASIST community.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
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 score0.976
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0190.013
Scholarly communication0.0240.026
Open science0.0030.013
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0190.004

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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2006
Admission routes1
Has abstractyes

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