Religious Language and Critical Discourse Analysis: Ideology and Identity in Christian Discourse Today, by Noel Heather
Bibliographic record
Abstract
Severe, under-treated pain has profound, far-reaching effects on the pa tient.One of the main themes of the book is the close relationship between pain and the desire to die, and between pain management (analgesia) and the will to live.An article by Sylvia D. Stolberg included in Death Talk is a rebuttal to the pro-euthanasia position, refuting the claim that "human dignity is lost through disability, disease, dependency, or suffering.Human dignity is not a thing that can be lost, and [to think so] involves an impoverished interpreta tion of human dignity" (256).She makes the pivotal point that the pro euthanasia debate assumes that dignity is socially-determined judgment, and not, as she believes, an intrinsically human value-an inextricable aspect of human nature.Death Talk suggests that it is perhaps our fear of death that elicits a need to control it, and that perhaps euthanasia deprives us of unique, meaningful, transcendental experiences that can enrich our understanding of existence and death.In the final analysis, we will all find ourselves in the dilemma of eutha nasia, and "We all hope to be included among those who have 'good deaths'" (25).
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.045 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| 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".