Constructing a didactic model of detective short stories
Bibliographic record
Abstract
In order to contribute for the training of teachers on the issue of teaching textual genres, this article focuses on the conception of a didactic model of the genre detective short stories adapted to the process of learning the Portuguese language in Brazil and in Portugal. The proposal is based both on the theoretical reflection on this genre, in the fields of Textual Linguistics and Literature, and on the linguistic analysis of the text that it adopts (“The Adventure of the Beryl Coronet”, in The Adventures of Sherlock Holmes, by Sir Arthur Conan Doyle). The analysis focuses on the most relevant aspects that characterize the textual genre, according to its social functioning, which include the interaction, among thematic, organizational and enunciative aspects.The deriving didactic model of genre based on the above referred aspects (henceforward referred to as MD) will neither neglect the identification of what can be taught in higher education (3rd and 4th Ciclos, in the case of Brazil, and 2nd and 3rd Ciclos, in the case of Portugal) nor the question of the progression in learning. We will emphasise the theoretical and methodological framework of Sociodiscursive Interactionism (henceforth referred to as ISD), in particular the textual architecture model proposed by Bronckart (1999) and the MD, developed by the groups GRAFE and ALTER (with special reference to Dolz and Schneuwly 1996, 1997, 1999; Schneuwly et al., 2004; De Pietro et al., 1996; Machado and Cristóvão, 2006; Machado, 2009). Key words: detective short story, Didactic Model of Genre (MD), Sociodiscursive Interactionism (ISD).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".