A Practical Theology of Funeral Preaching
Bibliographic record
Abstract
Christian ministers increasingly recognize that traditional funeral practices no longer connect with contemporary audiences as they once did. While pastors continue to affirm the importance of funerals and funeral sermons, especially for Christian communities, many struggle with how best to conduct these rituals in a rapidly changing religious landscape. This dissertation seeks to help preachers better understand their audiences by identifying the prevailing beliefs about a funeral’s purpose and significance for mourners. By analyzing these beliefs, the study aims to help funeral preachers anticipate potential obstacles to communicating the Christian gospel to mourners, allowing them to adapt their preaching accordingly. As a work of practical theology, this dissertation seeks to develop funeral preaching as a research-led practice. It employs two qualitative research methods: qualitative content analysis of obituaries and phenomenological interviews with funeral professionals. The dissertation then examines the findings in dialogue with nontheological theories, such as Ernest Becker’s theory of the denial of death. It reflects upon both the qualitative evidence and the non-theological interpretations using the theology of the cross. The study then offers recommendations for refining the practice and content of funeral preaching to help the funeral sermon better connect the life of the deceased with the gospel of grace and so comfort mourners with the death and resurrection of Jesus Christ.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.061 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".