Women’s Participation in Nigeria’s Industrial Development Process: Obstacles and Options for Change
Bibliographic record
Abstract
Development is a multifaceted phenomenon. In all its forms, it involves the positive transformation of all aspects society, hence the relentless investment of efforts by all societies to achieve it. Achieving development generally, and industrial development in particular, requires the effort of everyone, including women. For Nigerian women, taking up this all important responsibility has been more or less like swimming against the tide, due to the interaction of various social, cultural and biological factors. This paper x-rays the relevance of women to Nigeria’s industrial development, drawing attention to some of the obstacles to their optimal and effective participation in the process. Furthermore, the paper explores available options for change, and concluded that only when women are allowed to actively participate in industrial development via the removal of the identified obstacles, that the industrial and other forms of development in Nigeria can take a turn in the direction of meaningful success.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 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".