Philosophical orientations and theoretical frameworks in media effects
Bibliographic record
Abstract
Abstract This paper explores the philosophical orientations within which agenda setting operates, and agenda setting’s place within the broader framework of the media effects tradition, specifically in comparison with framing and priming. It also responds to earlier criticisms of agenda setting for its supposed lack of theoretical richness and narrowly understood underlying mechanisms. Both ontological and epistemological statuses of the agenda-setting theory are analyzed in order to place agenda setting into the communication discipline’s broader context. This paper demonstrates that the most important distinction between framing and agenda setting is that they are based on different ways of knowing. While the epistemological bases of priming are similar to the theory of agenda setting, the paper argues that further progress will depend not only on practical studies of different aspects of agenda setting, but also on theoretical and philosophical conceptualizations in the future.
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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 | 0.023 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.004 | 0.060 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".