Genre Variation and Changes in Frame Sequences Across Cultures: The Case of Criminology RA Abstracts in English and French
Bibliographic record
Abstract
Abstract Though not as widely studied as the Research Article (RA), the abstract has attracted increasing interest among researchers over last decades (Swales 1990, Bhatia 1993, Dos Santos 1996, Lorés-Sanz 2008, Bondi/Cavalieri 2012, Cavalieri 2014). A number of contrastive or comparative studies of abstracts in English and other languages (Martín-Martín 2005, Lorés Sanz 2006, Van Bonn & Swales 2007, Diani 2014) have already been carried out considering mainly the hard sciences and some soft sciences such as linguistics and history, however no cross-cultural analyses have been conducted so far between RA abstracts in English and RA abstracts in French published in the legal field. This paper seeks to investigate genre variation and changes in frame sequences comparatively in English and French RA abstracts from criminology journals. Using a genre analytical approach to qualitative and quantitative data, the paper reports on two comparable corpora, i.e. English and French, of electronically retrieved abstracts from Criminology Journals published in 2014. The two corpora are composed of three journals per language, namely Criminology, Journal of Criminal Justice, Journal of Criminal Law and Criminology for the English corpus, and Champ Pénal, Criminologie, Revue Canadienne de Droit Pénal et Criminologie for the French corpus. The analysis will be carried out following two main steps, i.e. a macro-analysis and a micro-analysis. In the former step, the corpora are compared by the analysis and discussion of the basic IMRD rhetorical move structure for the RA often proposed in the literature (e.g. Nwogu 1990; Swales 1990; Bhatia 1993; Ventola 1994; Martín-Martín 2002) and the additional five moves model postulated by Dos Santos (1996) with the aim of investigating the linguistic and rhetorical variation in the abstract genre from a cross-cultural perspective. In the latter, we look at frame sequences (Bondi/Cavalieri 2012) combining forms of self-mentions and frame markers (Hyland 2005), i.e. personal patterns (e.g. we argue / nous questionnons), impersonal patterns (e.g. it is argued / il est question) and locational patterns (e.g. the paper argues / l’article questionne) (Dahl 2004). Provisional results show that the abstracts under investigation largely follow the international conventions based on the norms established by the English-speaking international academic community. However, variation across the two cultures emerged from the linguistic realizations of framework sequences. Cross-cultural implications are discussed at the close.
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 | 0.011 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".