Beyond the watery grave: death and water reminders as (un)expected ways to increase environmental identity / <i>Más allá de la tumba acuática: recordatorios de muerte y agua como formas (in)esperadas para fomentar la identidad ambiental</i>
Bibliographic record
Abstract
Climate change increasingly stresses global water availability and reliability via either too much (e.g., floods) or too little (e.g., droughts). To ensure safe and equitable water access and management, significant behaviour changes are needed among both water consumers and decision-makers. Yet discussing water vulnerabilities can be existentially threatening because these water crises involve considering potential physical harm or death from a life-sustaining resource. According to Terror Management Theory (TMT), implicit or explicit awareness of existential threats may result in contradictory identity reinforcements that may actually limit positive water solutions. We examined how three life-threatening water messages — specifically drowning, contaminated water consumption, dehydration — influenced environmental identity compared to a standard mortality threat and a control among 455 Canadian and American adults. Our results indicated that existentially threatening messages significantly increased environmental identity polarization ( p < .05). Given these findings, we discuss implications for sustainable water management within an increasingly threatening global environment.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".