The language used in describing autobiographical memories prompted by life period visually presented verbal cues, event-specific visually presented verbal cues and short musical clips of popular music
Bibliographic record
Abstract
Here, we examined linguistic differences in the reports of memories produced by three cueing methods. Two groups of young adults were cued visually either by words representing events or popular cultural phenomena that took place when they were 5, 10, or 16 years of age, or by words referencing a general lifetime period word cue directing them to that period in their life. A third group heard 30-second long musical clips of songs popular during the same three time periods. In each condition, participants typed a specific event memory evoked by the cue and these typed memories were subjected to analysis by the Linguistic Inquiry and Word Count (LIWC) program. Differences in the reports produced indicated that listening to music evoked memories embodied in motor-perceptual systems more so than memories evoked by our word-cueing conditions. Additionally, relative to music cues, lifetime period word cues produced memories with reliably more uses of personal pronouns, past tense terms, and negative emotions. The findings provide evidence for the embodiment of autobiographical memories, and how those differ when the cues emphasise different aspects of the encoded events.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".