Rhetorical Strategies in Selected Nigerian Print Media Advertisements
Bibliographic record
Abstract
The study “Rhetorical strategies in selected Nigerian print media advertisements” sought to investigate the interconnectedness between rhetoric and advertising. Privileging Aristote’s theory of rhetoric (1991), Halliday’s (2014) Systemic Functional Linguistics (SFL) and van Dijk’s (1993) Socio-Cognitive Approach (SCA) as theoretical frameworks, the study which adopted a descriptive qualitative case study research design and a purposive data collection method carried out a linguistic stylistic analysis as well as a critical discourse analysis of the selected data. The findings from the linguistic stylistic analysis showed that advertisers deploy various attractive and attention-seeking rhetorical strategies at the different levels of linguistic analysis in order to grab the interest and attention of the listener, while the critical discourse analysis revealed that the rhetorical strategies are employed as persuasive devices to cause a change in the buying choices and behaviour of customers. The critical discourse analysis further revealed that the advertisements aside selling a product also communicate socio-cultural values and ideologies. The study concluded amongst other things that rhetoric is a significant component of advertising and that the rhetorical strategies prevalent in the linguistic analysis of the advertisements function as persuasive elements that inform about the availability of goods and services as well as function in transmitting the socio-cultural values and ideologies of the environment in which they are created.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".