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Record W1940532203 · doi:10.1002/bult.2013.1720400105

Selected ASIS&T board members discuss research trends in information science: A summary

2013· article· en· W1940532203 on OpenAlexaffabout
Rhiannon Gainor

Bibliographic record

VenueBulletin of the American Society for Information Science and Technology · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsMcGill University
Fundersnot available
KeywordsCreativityBig dataInformation scienceEngineering ethicsEditorial boardPersonal information managementPersonally identifiable informationComputer scienceData scienceInformation systemPublic relationsKnowledge managementSociologyLibrary sciencePsychologyPolitical scienceManagement information systemsEngineering

Abstract

fetched live from OpenAlex

Abstract Editor's Summary A symposium organized by McGill University's iSchool students and director brought together past, current and future ASIS&T presidents and board members to discuss trends in information science research. The discussion revealed diverse opinions on the definition of information science, concerns about research practices and expected directions for future research. Definitions of the field focused on social questions in an information society, the intersection of information and technology and strategies to better connect information with users. Panelists exhorted attendees, many being students, to tackle big questions, consider the applications of their research and collaborate with other disciplines. The critical role and strength of information science should drive robust and compelling research, addressing areas of need from the personal to the national level. Specific topics needing investigation include big data, information security, information as a stimulus for creativity, personal information management and better integration with technology.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.018
Science and technology studies0.0010.007
Scholarly communication0.0000.005
Open science0.0010.001
Research integrity0.0000.000
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 head0.040
GPT teacher head0.321
Teacher spread0.281 · 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 designNot applicable
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

Citations1
Published2013
Admission routes2
Has abstractyes

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