Event Models: A Socio-cognitive Study of Selected Interrogations in 2008 Quasi-judicial Public Hearing on Federal Capital Territory (FCT) Administration in Nigeria
Bibliographic record
Abstract
This study carries out a socio-cognitive analysis of 2008 national quasi-judicial public hearing on Federal Capital Territory (FCT) in Nigeria. Video recordings of interrogations between the public hearing panel and complainants/defendants were used as data for the study, which were taken from the 2008 national public hearings on FCT administration in Nigeria. Van Dijk’s sociocognitive approach to Critical Discourse Analysis (CDA) was used in the analysis of the data. Twenty randomly sampled interrogations were recorded and transcribed. The event models of the interactants featured global topics and local semantics, argumentative and rhetorical strategies. These are influenced by protective, suppressive, defensive and restorative ideologies. The study helps in the understanding of public hearing interrogations as it gives one the knowledge of how ideologies can shape linguistic and semantic patterns in a text. Key words : Critical discourse analysis; Sociocognitive; Ideologies; Event models; Quasi-judicial Public Hearing
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".