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Record W2298677131 · doi:10.5539/cis.v9n2p10

Conceptual Model of Technological Change on Telecentre Effectiveness

2016· article· en· W2298677131 on OpenAlexvenueno aff
Zahurin Mat Aji, Nor Iadah Yusop, Faudziah Ahmad, Azizi Ab Aziz, Zaid M. Jawad

Bibliographic record

VenueComputer and Information Science · 2016
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
FundersUniversiti Utara Malaysia
KeywordsProcess (computing)Computer scienceConceptual modelTechnological changeQuality (philosophy)Operations managementEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Telecentre effectiveness is highly related with involvement of people in the community and has been measured by the socio-economic benefit gained from the telecentre. One of the important aspects that are often overlooked in the assessment of telecentre effectiveness is the technological change. It is referred to as the overall process of continuous invention, innovation and diffusion of technology that aims at improving the quality of telecentre operations. This paper presents a conceptual model of technological change on telecentre effectiveness. In achieving this, extensive reviews of literature on related concepts were performed. Several elements of technological change that are expected to have impact on telecentre effectiveness were identified. These elements were categorized into three dimensions of technological change process, which are in accordance with the Linear Model of Innovation namely invention, innovation and diffusion. This model can be used as a basis towards getting empirical evidence on the impact of technological change on telecentre operations.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.006
Scholarly communication0.0070.011
Open science0.0020.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.237
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2016
Admission routes1
Has abstractyes

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