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Record W1954076670 · doi:10.15353/joci.v3i2.2377

Overnight Internet Browsing Among Cyber Café users in Abraka, Nigeria

2007· article· en· W1954076670 on OpenAlexvenueno aff
Esharenana E. Adomi

Bibliographic record

VenueThe Journal of Community Informatics · 2007
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetService (business)Internet accessInternet privacyWorld Wide WebBusinessComputer scienceMarketing

Abstract

fetched live from OpenAlex

This paper is a survey of overnight browsing service use in cyber cafés located in Abraka, Nigeria. Data were collected by means of questionnaire from 61 clients who were in 5 cyber cafés to make use of the overnight Internet access service, while frequency counts and percentages were used to analyze the data. It was revealed that a majority of the users (59%) were males, the age range of 21-25 ranked first (50%) as users of the service with students as the major users. It was also discovered that 60.7% of the respondents use the overnight Internet service to enable them have enough time to explore the services and resources of the Net; computers/internet response ranked first as a factor which determine the cyber café used for the service, 68.8% of them seek information to supplement their course work during the overnight service but sleep is a constraint faced by most of the clients followed by inability to open some sites/web pages. It is recommended that cost of internet access be reduced to NGN30.00 per hour to encourage cyber café users to use the internet for long duration during the day and individuals/organizations should archive their documents/files to prevent site disappearance.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.265
Teacher spread0.239 · 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 designObservational
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

Citations18
Published2007
Admission routes1
Has abstractyes

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