Telecommunication Masts/Base Transceiver Stations and Regulatory Standards in Abia State, Nigeria
Bibliographic record
Abstract
<p>Global System for Mobile Communications (GSM) was introduced in Nigeria in May, 2001. Since then, GSM subscriber base has grown astronomically leading to the indiscriminate installation of Masts and Base Transceiver Stations across the country. The Nigerian communications commission (NCC) and the National Environmental Standards and Regulations Enforcement Agency (NESREA) established environmental standards in 2009 and 2011 respectively to regulate the installation of BTSs and Masts. This study examined the compliance of GSM service providers with the established guidelines for the mounting of BTSs and Masts in Abia State, Nigeria. The study adopted geometric survey technique, and relied mainly on primary data which were collected through direct observation and measurements. Cluster and simple random sampling techniques were used to proportionately select BTSs/Masts that were surveyed. Data collected were analyzed with appropriate parametric tests using SPSS for Windows, Version 17. Specifically, the <em>t </em>test for paired samples, and Analysis of Variance (ANOVA) were used to test the hypotheses of the study. The results show that there is significant difference between the mean value of the number of BTSs/Masts surveyed and the mean value of the number that complied with regulatory standards. The study further revealed that there were no significant differences between the telecommunication networks in their application of the environmental standards. The researchers therefore recommend that both NCC and NESREA be made to devolve their supervisory and monitory responsibilities to Town Planning Authorities at the local government level to ensure effective enforcement of the regulatory standards. </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".