How to communicate “long term”? 10, 100, 10,000 years …? Practice, research, reflections
Bibliographic record
Abstract
Some environmental issues (nuclear/special wastes, CO2 storage) are extremely long-lasting, from thousand to one million years (Flüeler 2023). Three aspects are mandatory to recognise them adequately: their complexity (e.g., safety “proof”), uncertainty (aleatory/epistemic …), inequality (today’s risk deciders vs. future risk bearers). All require a deep sense of multiperspectivity: Changing perspectives enables a conscious view of an issue from different angles.With exceptions, conventional practice reveals “technical” and “acceptance” approaches. The problem is said to be solely political, “the public’s” poor state of knowledge spurs the plea for “outreach”, following the “deficit model”: Specialists inform laypeople to close their “information gap”. The long term is covered by safety margins and, as a last resort, by waste retrievability.Applied research is more sophisticated. Nuclear waste safety cases have become comprehensive, considering insecurities and stakeholder involvement (NEA 2020b). Still, the very long term (10,000y plus) is left to risk analysts. “Communication Across 300 Generations” (Tannenbaum 1984) or “to bridge ten millennia” (Sebeok 1984) are issues reserved to semiotics and not really developed further (NEA 2019). Conserving artefacts and symbols over time seems unsatisfactory, even unrealistic. Site-selection procedures have, partly, recognised the need for decades-long processes (NEA 2020a).What is “long term”? (cf. Flüeler 2023, 55ff.) It would be futile for society to deal with the year 800,000 AP, but it is to reckon what Brand and Eno called “the Long Now”, https://longnow.org: 10,000 years back and forth, yet a generations-based approach seems more practical, maybe the Canadian First Nations’ yardstick of the Seven Generations (NCSL 2017): “Traditionally, no decision was made until it was understood how it would affect the next seven generations”. Or we draw on Boulding’s suggestion: 100 years backward and foreward (grandparents to grandchildren) (Boulding 1978).At any rate, our responsibility to future generations “requires new operationalisations, new norms of practice, new sets of values, new virtues, and – last but not least – new institutions” (Birnbacher 1988). It needs new skills for sustainable governance, transparent (digital) dashboards, open online platforms to table/respond to controversial views/assertions, transdisciplinary labs, ways to address indeterminacy (>>“uncertainty”), VR learning machines to train changing perspectives, etc.The ethical, political and institutional complexity insinuates that there is no silver bullet to tackle the issue of governance: “The solution is easily summarized, but much less easily achieved: to establish ecological reflexivity as a core priority of social, political and economic institutions” (Dryzek/Pickering 2019). We need continual discourse to transform our societies sustainably, rather than pre-fixed concepts in order to restore supposedly paradisiac past states.____________________Birnbacher, D. Verantwortung für zukünftige Generationen. Reclam, Stuttgart (transl.).Boulding, E. The Family as a Way into the Future. Pendle Hill, Wallingford, PA.Dryzek, J.S./Pickering, J. The Politics of the Anthropocene. Oxford Univ. Press, Oxford.Flüeler, T. https://doi.org/10.1007/978-3-031-03902-7.NCSL. https://healingofthesevengenerations.ca/about/history.NEA/Nuclear Energy Agency/2019. Preservation of Records, Knowledge and Memory Across Generations. OECD, Paris.NEA/2020a. Final Disposal of Radioactive Waste. Policy Brief.NEA/2020b. Two Decades of Safety Case Development: An IGSC Brochure.Sebeok, T.A. Communication Measures to Bridge Ten Millennia. BMI/ONWI-532. Battelle, Columbus, OH.Tannenbaum, P.H. Communication Across 300 Generations: Deterring Human Interference with Waste Deposit Sites. BMI/ONWI-535.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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; both teacher heads agree on what is shown here.
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".