Moralizing Uncertainty: Suspicion and Faith in Hitchcock's <i>Suspicion</i>
Bibliographic record
Abstract
This paper presents a phenomenology of suspicion by way of a close reading of Alfred Hitchcock's 1941 film, Suspicion. The main argument of the paper is that suspicion is an interpretive strategy that can be used for making sense of situations that appear ambiguous or uncertain. In developing this argument, I claim that suspicion and faith are actually related interpretive experiences, a point that is articulated in the film although it is generally overlooked. Faith and suspicion may be equally paradoxical conditions, but they are essential strategies by which the world is interpreted and uncertainty is domesticated.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.045 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".