Experimental Manipulation of Beliefs about Uncertainty: Effects on Interpretive Processing and Access to Threat Schemata
Bibliographic record
Abstract
This study investigated the influence of beliefs about uncertainty on interpretive biases and access to threat schemata, with the use of an experimental manipulation. Individuals from the community and undergraduate students (N = 74) were randomly assigned to one of two experimental conditions: positive beliefs about uncertainty (n = 37) and negative beliefs about uncertainty (n = 37). To manipulate beliefs about uncertainty, participants watched a presentation on problem solving that either contained information about the positive or the negative effects of uncertainty on problem solving. To assess interpretive biases, participants completed a modified version of the Ambiguous/Unambiguous Situations Diary. Participants read potentially threatening passages and rated their level of worry. Passages were then disambiguated either positively or negatively and participants rated the likelihood and the value (goodness or badness) of these events. To assess access to threat schemata, the Catastrophizing Interview was administered. The Catastrophizing Interview is a structured worry task that assesses various aspects of the worry process, using the downward arrow technique. The results indicated that, although many of the expected group differences were not observed, participants in the negative beliefs about uncertainty group did rate the positively disambiguated scenarios as less positive and the average likelihood of feared consequences to personal worries as more probable. This study provides partial support for the notion that beliefs about uncertainty may have a causal effect on interpretations of ambiguous situations as well as on ease of access to threat schemata.
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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".