MétaCan
Menu
Back to cohort
Record W113155598

Using an information ecology approach to identify research areas: Findings from Lithuania

2009· article· en· W113155598 on OpenAlexfundno aff
Vida Beresnevičiūtė, Eglė Butkevičienė, Elena Macevičiūtė, Renata Sadunišvili

Bibliographic record

VenueResearchWorks at the University of Washington (University of Washington) · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicData Quality and Management
Canadian institutionsnot available
FundersInternational Development Research CentreUniversity of WashingtonBill and Melinda Gates Foundation
KeywordsEcologyGeographyEnvironmental resource managementEnvironmental planningEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

The material presented in this report is related to the experiences and findings of exploratory fieldwork activities carried out in Lithuania for the Global Impact Study of Public Access to Information and Communication Technologies. The main objectives of this exploratory fieldwork are related to collection of background information and data on practices of usage of public access to ICTs on the basis of which research questions could be generated. Also, this activity has objectives of piloting both certain research approach and instrumental aspects of research development. The activity was both descriptive and exploratory. Having in mind the overall objectives of the project the following research questions were formulated for this initial phase: - What role(s), that public venue ICTs play in the communities of users, can be identified at present? What problems are visible in their operation? - Are there any obvious differences in the ways of operating and using the public access ICT in different sites (e.g., rural/urban, solitary/one of several, big city/small town, library/internet café, etc.)? - Who are the main users of the public ICTs? What are their purposes and practices of using public access ICT’s? - What is the general information usage context, into which the public ICTs use is embedded? The general approach of the exploratory research emphasize the phenomenological approach towards the measuring social impact of public access to ICT aiming at disclosing the affect to experiences of individuals and communities.

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)0.015
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0000.004
Open science0.0060.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.225
GPT teacher head0.403
Teacher spread0.178 · 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 designQualitative
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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueResearchWorks at the University of Washington (University of Washington)Same topicData Quality and ManagementFrench-language works237,207