Mass Observation and the Emotional Energy Consumer
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
Understanding how people lived with energy in the past is becoming increasingly important as policy-makers are paying more attention to the social and cultural factors that condition energy consumption and fix energy demand. This is challenging historians to demonstrate the ways in which energy systems are more than just physical infrastructures set into the built environment but activated by users with complex emotional lives. This article goes some way toward developing this history, building up a profile of the emotional energy consumer. To do this it draws upon a collection of material from the Mass Observation Archive (MOA), University of Sussex, which provides unique access to the emotions British users brought to their energy systems. Drawing upon a series of Directives written in the late 1980s and the early 1990s, the article considers how energy demand was shaped by the complex emotional cultures of Thatcherite Britain. The article proposes two different approaches to do this. The first approach considers how observers rooted emotions about energy in longer individual and social timeframes. This uncovers the importance of time in fostering emotions toward energy, from the lived experience of transitions, to the social memory of World War II and circulating rhetoric about the future. The second approach considers how emotions — such as sentimentality, nostalgia, love and fear — structured energy choices and led to particular configurations of energy use in the home. By demonstrating how emotion mediated between observers and their energy systems this article argues for the necessity of developing histories of energy focussed not only upon energy systems but that centre the complex subjectivities of users as well as their emotional cultures.
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 | 0.000 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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