Why is it so hard to think about the future? An autoethnographic exploration of future thinking and the future self
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A recent survey revealed that most people do not think about the far future. Most respondents rarely or never thought 30 years into the future, and about 27% rarely or never think even five years ahead (Institute for the Future, 2017). This has major impacts for society, especially with regards to long-term issues such as climate change. This project explores the barriers to thinking about the future with the aim of investigating how more people might be enabled to participate in future-thinking activities in ways that are both empowering and appropriate to them. Furthermore, an autoethnography-guided literature review explores how people might foster stronger relationships with their future selves such that they (and society) can better act in the present towards beneficial long-term goals. \n \nThe project work culminates in the proposal of five recommendations for those interested in future thinking. The hope is that these will inspire both those who are beginning a personal future thinking practice and foresight practitioners attempting to understand the challenges people face when they are asked to think about the far future.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it