Lack of Consumer Awareness: A Major Challenge for Electricity Consumer Protection in Nigeria
Bibliographic record
Abstract
Purpose: This study explores the challenges for consumer protection in the Nigerian deregulated electricity sector. The study argues that ignorant and unenlightened consumers are easy prey for exploitation in the marketplace. Educating the consumer minimizes consumer exploitation and enhances consumer protection. Design/methodology/approach: The study is qualitative. Twenty in-depth semi-structured interviews were conducted with the relevant stakeholders involved in consumer protection and standard setting in the Nigerian electricity sector. The study adopted the Benner’s Interpretive Phenomenology and explored the everyday practical experience and perspectives of the participants on the challenges of consumer protection. The analysis was thematically conducted and accordingly supported by sufficient excerpts. Findings: The study found several challenges for consumer protection in the Nigerian electricity sector. Emphatically, the participants were unanimous on lack of awareness as the major challenge for the electricity consumers’ protection. Research limitations: The research participants were only staff from consumer protection and products standard setting agencies, academics, and heads of consumer organizations. Additionally, the paper only addressed the challenge of lack of awareness and the data collection constrained by funds paucity and difficulties in securing appointments with the busy participants. Practical implications: The study suggests that consumer protection agencies need to do more in the area of consumer education and enlightenment otherwise the exploitation of the Nigerian electricity consumers will continue. Originality/value: Consumer protection literature abounds. This study is, however, the first attempt at qualitatively exploring in-depth the challenges for electricity consumers in deregulated electricity sector. The study emphasized the value of consumer awareness for better consumer protection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".