ON THE INVISIBLE SOCIO-TECHNICAL SYSTEMS – THE GREAT UNKNOWN
Bibliographic record
Abstract
Energy is an important resource in society and we often depend on energy in our everyday life. Energy-related emissions constitute at the same time a major environmental load, and we need to use energy more efficiently. To develop sustainable energy systems users need to transform their behaviour and start reflecting on their energy use. The aim of this paper is to discuss different methods to visualize energy use in households. We will discuss experience from three different methods, namely information, time-diaries and a power-aware cord. Every method has its drawbacks, but combining the three methods could be one way to highlight households' energy use and their possibility to energy conservation. By using the results from the introduction of time-diaries and technical artefacts in households when developing information campaigns and in energy guidance, we can find strategies that appeal more closely to peoples' behaviour, hence making it easier for households to put the advice into practice in their everyday lives.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.076 |
| Scholarly communication | 0.016 | 0.029 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".