Clash of Identities and Ethno-Religious Conflict in Kaduna State Nigeria
Bibliographic record
Abstract
Over time Clash of Identities in Kaduna North-west Nigeria often manifest into ethno-religious conflict in the state. This paper examines however the nexus between politics, ethno-religious and sharp identity question that formed the basis of ethno-religious conflict in the area. These however, affect sustainable development in Kaduna state. Historically, this conflict has played itself out in the contest for space, resources and access to power between different communities in the state; it also accesses how state failure and elite competition for power and resources in a multi-ethnic nation causes ethno-religious conflict and sharp identity question in Kaduna state. The paper adopts Human Needs theory. This theory explicates the reason to meet basic needs of man and if these needs are not met, conflict is likely to occur. The paper also adopts qualitative methods of data collection; this is drawn from both primary and secondary sources of data. It utilizes instrument of in-depth interviews with the key actors, community leaders and religious leaders. It is the finding of the paper that politics of identity and ethno-religious conflict have been the fundamental issue that poses security challenges to Nigeria. These challenges have taken the form of bombing, injury; killing and kidnapping that threatened Nigeria national security. The study recommends that government; ethno-regional and religious groups should adopt preventive diplomacy and dialogue to attaining cohesion and symbiotic relationship.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".