Bibliographic record
Abstract
(From the Introduction) Metal music means everything to me. It has been the main focus of my life since the age of thirteen. What first drew me to Metal still excites me about it today; guitar riffs. The sheer power of Marshall amplifiers gives me the same thrill it did when I first experienced Metal. My best friend gave me a CD by the band Megadeth called “Rust in Peace”. The opening riff of this album still gives me chills. From that moment on I knew I wanted to know more about Metal; everything from seminal albums, to its history. I am still learning more about the music, which presently involves piecing together Canada’s Metal music history. Why Canadian Metal? I’ve never felt attached to other aspects of Canadian culture, and so Metal music is my opportunity to do so. When I began my undergraduate degree at Queens university, I started a radio show called “Metal on Metal”. “Metal on Metal” is dedicated to all sub-genres of Metal. I noticed that the more I did the show, the more Canadian Metal I was playing. For me, working in community radio gave me a voice, and a confidence that made me feel comfortable expressing my view point on a variety of issues, and being comfortable with public speaking. I felt a need to document as much Canadian Metal history as I could. As such, one of my biggest motivations for this project has been the desire to capture and tell the stories of some of my favorite Canadian bands. So far, during the course of this project, two Toronto bands have disbanded; Dead Mouth and Teethmarks. It was important to visually document the music. These bands are important to me, and an integral part of Canada’s musical identity because they represent a whole cultural movement. The most important thing for me, however, is to showcase the music’s importance on a larger cultural scale; how it contributes and enhances Canadian culture. Before analysing the the film itself, I feel the title should be explained. Heavy Metal Thunder was the first time the phrase “Heavy Metal” was first said by the group Steppenwolf, a Canadian rock band. The song “Born to be Wild”, a biker anthem from the 1960’s about counterculture, has been argued to be the first Metal song ever. I felt this was important because it ties Canada’s roots back to the origins of Metal itself. In it reference to the process of purifying and perfecting physical objects, the title also incorporates the alchemical aspects in my film. By defining the technical terms necessary when critiquing music, this paper will give the reader insider knowledge of Metal music. I will then examine the areas of research, by conducting a literature review of scholarly texts, and assessing the documentary relevance intandem with a Metal documentary review. I will then discuss the central themes of my film Heavy Metal Thunder, and break down the methodology in making this film. Finally, I will situate each Metal sub-genre as it stands in Canada.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".