Bibliographic record
Abstract
The overall purpose of the study is to make visible various aspects of CDA. It presents various approaches to discourse analysis and critical discourse analysis to justify the adoption of certain models over others. A general theoretical account of the various influential approaches to the text will be presented first, followed by a critical approach next to arrive at their range of usefulness as a means to an end. Besides the absence of a general terminological consensus among text linguists, the fact is that there is no one generally accepted theory of discourse analysis that undertakes to provide the complete analysis of texts. While all text analysts acknowledge the fact that a text has structure, coherence, function, organisation, character and development, their approaches differ as to how each of these properties is realised and mutually related to other properties, hence the advantages of the eclectic approach which provides for the necessary step of integrating a variety of compatible systems of discourse analysis whenever these are found useful and adaptable to the requirements of each study. Such an approach, while lessening the problems of indeterminacy and partiality, remains just one model yielding one specific interpretation. However, variation in interpretations is resorvable and can ultimately be made definitive given a text and the same vital background information and approache(s).
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.012 | 0.056 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".