Impacts of family household dynamics on residential energy demands in Hebei Province of China
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
Abstract This article presents analyses and projections of the residential energy demands in Hebei Province of China, using the ProFamy extended cohort-component method and user-friendly free software and conventional demographic data as input. The results indicate that the future increase in residential energy demands will be dominated by large increase in small households with 1–2 persons. We found that increase of residential energy demands will be mainly driven by the rapid increase of older adults’ households. Comparisons between residential energy demand projections by household changes and by population changes demonstrate that projections by population changes seriously under-estimate the future residential energy demands. We recommend that China needs to adopt policies to encourage and facilitate older parents and adult children to live together or near-by, and support rural-to-urban family migration. Promoting inter-generation co-residence or living near-by between older parents and young adults would result in a mutually beneficial outcome for both older and younger generations as well as to effectively reduce energy demands. We suggest governments to carefully formulate strategies on efficient residential energy use to cope with the rapid households and population aging, and strengthen data collections/analyses on household residential energy demands for sound policy-making and sustainable development.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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