Images of Essence: Journalists’ Discourse on the Professional “Discipline of Verification”
Bibliographic record
Abstract
The verification of factual accuracy is widely held as essential to journalists’ professional identity. Our rhetorical analysis of interviews with award-winning and semi-randomly selected newspaper reporters confirms this professional norm while revealing a preference for four types of image to describe verification methods. Spatial and temporal travel images paint verification as an embedded but adaptable heuristic process. Images of conflict suggest verification as a weapon and a shield against implied enemies. Journalists speak of vision both literally as the preeminent tool of verification, and figuratively as a metaphor for interpretation. Meanwhile, a fourth and seemingly predominant image—that of storytelling—functions to integrate the images of travel, battle, and observation and the different forms of professional identity that they connote. The quest for truth through storytelling likewise suggests a rich, if ambiguous, sense of good journalism as combining the instruments of fact with the craft of fiction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".