Reasoning about redundant and non-redundant alternative causes of a single outcome: Blocking or enhancement caused by the stronger cause
Bibliographic record
Abstract
Perceptions of the effectiveness of a moderate probabilistic cause are influenced by the presence of stronger alternative causes. One important idea is that this influence occurs because the strong cause renders the weaker one statistically redundant. Alternatively, the causes might be contrasted to each other, so the stronger cause may simply overpower perceptions of the weaker one. Causes may have the same polarity (e.g., two generative/excitatory causes or two preventive/inhibitory causes) or be of opposite polarity (e.g., a generative cause versus a preventive or inhibitory cause). Previously, we found that the presence of a stronger redundant alternative cause of the same polarity reduces causal judgements of the moderate cause (i.e., blocking occurs) but a stronger cause of the opposite polarity enhances judgements of the moderate cause (i.e., enhancement). Experiments 1 and 2 further explored these cue competition effects with redundant and non-redundant alternative causes (i.e., correlated versus independent alternatives). We generally found that blocking and enhancement occur with both redundant and non-redundant alternative causes. This is inconsistent with an information processing view of cue competition that relies on statistical redundancy to account for blocking. Although these results are inconsistent with a redundancy information processing account of cue competition and are consistent with our earlier contrast account, we demonstrate here that a simple associative model can account for the sometimes apparently contradictory effects of cue competition.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".