Exploring Motivational Factors of Indigenous House Form for Value-Based Development: The Tiv People of Central Nigeria in Context
Bibliographic record
Abstract
The quest for contextual identity and value-based developments by concerned authorities justifies the necessity to explore the inherent motivating factors that influence housing formation and the built environments of the varied Nigerian ethnic groups. Rapoport's identification of socio-cultural values as the primary influencers of house form has come under scrutiny, stipulating a replication in different contexts. One tends to ask about the motivating factors for the indigenous house form of the different ethnic groups in Nigeria that need to be explored and harnessed for value-based planning, design, and development for future infrastructure. This study explores the motivating factors of the indigenous house form of the Tiv people of central Nigeria, filtered through Maslow's Hierarchy of needs. This qualitative study utilised the Means-End Chain soft laddering technique, where 24 participants were interviewed, analysed, and ranked. According to the findings, Tiv indigenous dwellings are circular-shaped, connecting them to their cultural heritage. The open compounds also permit communal interactions in their natural setting and express their determination to live independent family lives. For housing stakeholders in Nigeria, the primitive values evoked in this study are essential for developing a contemporary, culturally sustainable society.
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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 | 0.001 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".