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
The making of songs is an important, yet under-explored tradition amongst steel workers throughout North America. Steel making has been an essential part of Cape Breton Island’s economy and landscape since the mid-nineteenth century. The first steel mill was constructed in Sydney Mines in the 1870s; a larger mill was built in the newly emerging city of Sydney, the island’s largest centre, by 1901. Distinctive traditions of work and leisure began to emerge amidst the grid-patterned streets and company-owned homes of workers and managers. In the early years of the twentieth century, a close-knit working-class consciousness had taken root in the steel making centre of Sydney, Cape Breton Island. Songs explore topics such as the harsh conditions of work in the steel plant, personalities and places, tragedies, the industrial conflicts of the 1920s, and the attitudes of workers toward management. Many are often tinged with satire and witty analysis of working-class life. Sydney, as with many communities in North America, has profoundly experienced the process of deindustrialization in the latter part of the twentieth century. The last operating coal mines closed in Cape Breton the 1990s and the Sydney Steel plant shut its doors in 2000. This paper explores the questions: what role did songs about steel play in the development of class consciousness during the development of the steel industry in Sydney? Do songs play an equally significant role in the latter part of the twentieth century when the community was undergoing the process of deindustrialization? What types of songs about steel making and the steel mill are found in each of these significant periods in Sydney’s history? An exploration of some of these songs reveal much about how human beings respond to the processes of industrialization and deindustrialization.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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