An Examination of the Tenancy Agreement as a Shield in Property Management in Nigeria
Bibliographic record
Abstract
The purpose of this study is to critically examine tenancy agreement as a shield in property management in Nigeria. Renting is an essential component of a healthy housing system of a nation. It is observed that for most tenants, signing their tenancy agreement will be their largest financial commitment during the year; hence it is an issue not to be taken lightly. The rental housing sector in Nigeria is bedeviled with acute shortage of housing units (said to be between 14-17million units) this in turn impacts negatively on the sale and rental markets. The study revealed that tenancy agreement gives protection to the stakeholders in the rental housing sector only on paper. This is because many rental agreements between landlords and tenants in Nigeria are personal and informal in nature, concluded outside of any government regulatory framework or formal legal system. This informality and lack of official documentation makes going to court an extremely impractical way of dealing with landlord-tenant conflicts. The provisions of the rent control and recovery of premises laws in Nigeria have been held more in disobedience than in obedience for many years. For effective regulation of the rental property market in Nigeria, it was recommended among others, that a strategic approach to developing a workable rental housing policy should first acknowledge the rental arrangements which already exist and then find flexible, realistic ways to regulate and enforce them.
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 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 | 0.003 | 0.004 |
| 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 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| 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".