Threat and defense as goal regulation: From implicit goal conflict to anxious uncertainty, reactive approach motivation, and ideological extremism.
Bibliographic record
Abstract
Four studies investigated a goal regulation view of anxious uncertainty threat (Gray & McNaughton, 2000) and ideological defense. Participants (N = 444) were randomly assigned to have achievement or relationship goals implicitly primed. The implicit goal primes were followed by randomly assigned achievement or relationship threats that have reliably caused generalized, reactive approach motivation and ideological defense in past research. The threats caused anxious uncertainty (Study 1), reactive approach motivation (Studies 2 and 3), and reactive ideological conviction (Study 4) only when threat-relevant goals had first been primed, but not when threat-irrelevant goals had first been primed. Reactive ideological conviction (Study 4) was eliminated if participants were given an opportunity to attribute their anxiety to a mundane source. Results support a goal regulation view of anxious uncertainty, threat, and defense with potential for integrating theories of defensive compensation.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".