The reminiscence circumplex and autobiographical memory functions
Bibliographic record
Abstract
This study investigated the potential of a circumplex model to represent the functions of both reminiscence and autobiographical memory. Participants from four pre-existing data bases (i.e., Culley, LaVoie, & Gfeller, 2001; Webster, 1997, 2002; Webster & McCall, 1999) were combined, resulting in a total of 985 participants ranging in age from 17 to 96 (M age = 36.63 years). A total of 392 men (39.8%) and 591 women (60.1%), with two persons not reporting their gender, completed the Reminiscence Functions Scale (RFS) as part of the original four studies. The eight RFS factors were submitted to second-order factor analysis resulting in two orthogonal dimensions (self versus social and reactive/loss-oriented versus proactive/growth-oriented) accounting for 79.57% of the variance. Further, multidimensional scaling indicated that the original eight factors could be arranged in a circular fashion such that more closely related (i.e., more highly correlated) factors were placed closer together while factors less highly related were placed further apart. Advantages of a circumplex perspective for future theory and model development are illustrated.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".