Impediments to Entrepreneurship Development in the Niger Delta Region of Nigeria
Bibliographic record
Abstract
This study examines the issues and challenges to the growth of entrepreneurship in the Niger Delta region of Nigeria. This investigation was informed by the fact that governments, the world over, have in recent times strived to encourage the growth and development of entrepreneurship as an agent of economic transformation. This work therefore did a critical analysis of the challenges, with insight into their implications for the development of the Niger Delta region’s economy in particular and national economy at large. The study employed a survey research design and gathered data from both the primary and secondary sources. With the use of correlation statistics, it was found that lack of access to finance and poor infrastructural facilities (e.g. power supply) ranked first among other challenges that impede the growth of entrepreneurship in the Niger Delta region. Based on this, we recommended that a rural-development programme such as Entrepreneurial Skills Development (ESD) and institutions such as Small Business Development Centers (SBDC) should be established to educates villagers/Niger Deltans on the need for and advantages of innovations in their economically productive activities such as entrepreneurship while government is advised to shift its efforts and policies toward addressing these impediments especially the inadequate and deteriorated state of infrastructural facilities which are at the cradle of any meaningful advancement in entrepreneurship. It is by this that the growth of entrepreneurship in the region would be achieved. Key words: Entrepreneurship; Small businesses; Enterprise development
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".