‘Rising Number of Homeless is the Legacy of Tory Failure’: Discoursal Changes and Transitivity Patterns in the Representation of Homelessness in <i>The Guardian</i> and <i>Daily Mail</i> from 2000 to 2018
Bibliographic record
Abstract
Abstract Experts in different fields have claimed that the UK has experienced a process of growing economic inequality since the 1970s. Following Fairclough’s dialectal-relational approach, this paper presents a detailed, systematic analysis of the representation of homeless people and homelessness in The Guardian and Daily Mail from 2000 to 2018, in order to explore how these have been discursively represented over time. Therefore, our study addresses two specific research questions: How have homelessness and homeless people been represented in the UK press? Are there any discoursal changes in representation with the passing of time? The analysis, which has employed mostly qualitative but also quantitative (statistical) methods drawing on corpus-assisted discourse analysis, is informed by the theory of transitivity within Systemic Functional Linguistics. Results indicate that, within an overall negative representation of homeless people and homelessness in this period, there have been some significant discoursal changes over time. As such, this paper contributes to critical discourse studies and transitivity research on a relevant social problem, that of growing economic inequality in the UK.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".