Analysing Lexico-grammatical Features in Chimamanda Ngozie Adichie’s Americanah
Bibliographic record
Abstract
This article aims at carrying out an analysis of Chimamanda Ngozi Adichie’s Americanah (2013), using the Systemic Functional Linguistics (SFL). Such a linguistic approach views language as a strategic meaning-making resource (Halliday & Matthiessen, 2004; Eggins, 1994). The main and specific goal of the present study is to describe and analyse the lexico-grammatical features, characteristics of the language of Adichie’s Americanah . This leads to focus on the study of linguistic patterns such as Transitivity, Mood and Theme in three selected excerpts from the novel. The socio-cultural context of the production of the novel has made it easy to discuss and interpret the salient linguistic patterns which reveal the generic structure potential of the novel and has facilitated the study of how the novelist has woven her text as a message of alert through the depiction of such issues as immigration, love, race and identity in the context of today’s globalised world.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".