Bibliographic record
Abstract
Mental simulation, the process of self-projection into alternate temporal, spatial, social, or hypothetical realities is a distinctively human capacity. Numerous lines of research also suggest that the tendency for mental simulation is associated with enhanced meaning. The present research tests this association specifically examining the relationship between two forms of simulation (temporal and spatial) and meaning in life. Study 1 uses neuroimaging to demonstrate that enhanced connectivity in the medial temporal lobe network, a subnetwork of the brain's default network implicated in prospection and retrospection, correlates with self-reported meaning in life. Study 2 demonstrates that experimentally inducing people to think about the past or future versus the present enhances self-reported meaning in life, through the generation of more meaningful events. Study 3 demonstrates that experimentally inducing people to think specifically versus generally about the past or future enhances self-reported meaning in life. Study 4 turns to spatial simulation to demonstrate that experimentally inducing people to think specifically about an alternate spatial location (from the present location) increases meaning derived from this simulation compared to thinking generally about another location or specifically about one's present location. Study 5 demonstrates that experimentally inducing people to think about an alternate spatial location versus one's present location enhances meaning in life, through meaning derived from this simulation. Study 6 demonstrates that simply asking people to imagine completing a measure of meaning in life in an alternate location compared with asking them to do so in their present location enhances reports of meaning. This research sheds light on an important determinant of meaning in life and suggests that undirected mental simulation benefits psychological well-being.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".