Manitoba Hyrdro and Electricity Undertakings in Developing Countries: The Case of Nigeria
Bibliographic record
Abstract
he Nigerian government's invitation to Manitoba Hydro International Inc. ("Manitoba Hydro") to take over the management of the Transmission Company of Nigeria ("TCN") presents a mixed reality.First, the efficiency of Nigeria's electric power sector has, through over-centralized governance and administration, been made needlessly difficult and shrouded in secrecy.Also contributing to the challenges of the sector is the fact that Nigeria's power sector stands in close proximity to corruption, like its sister oil and gas industry.Manitoba Hydro has been invited by the Nigerian government to bid for the management of TCN. 1 The corporation's sound financial and technical bids were all the Nigerian government needed to achieve the desired breakthrough in its five-year search for competent firms to manage the most crucial of the successor companies formed in the wake of the electric power sector reforms which began in 2000.For Nigeria, electricity is indispensable to national growth and economic development, 2 and energy is widely acknowledged by energy LL.B (Ilorin), LL.M (Osgoode), Ph.D (Osgoode).Dr. Oke is a lecturer at the Faculty of Law at the University of Lagos in Nigeria.He has served as counsel for several leading law firms in Nigeria, and taught at York and Ryerson Universities. 1 See Remi Koleoso, "Federal Government, Canadian Firm in N3.7 Billion Naira Power Transmission Deal" Compass Newspaper (4 April 2012) 1, 8, and 12. See also Everest Amaefule, "Electricity: Canadian Firm Demands N3.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".