Making the Scene in the Garden State: Popular Music in New Jersey From Edison to Springsteen and BeyondDewarMacLeod. New Brunswick, New Jersey: Rutgers University Press, 2020.
Bibliographic record
Abstract
Scenes, musical and cultural, are the principal interests for distinguished scholar Dewar MacLeod in Making the Scene in the Garden State: Popular Music in New Jersey From Edison to Springsteen and Beyond. He reveals in the book's compelling introduction that the idea of “scenes”—their impact on each other and on the overall popular cultural history of New Jersey and America as a whole—is his scholarly concern. He argues that New Jersey's musical heritage has been unjustly overshadowed by better-known hotspots like New York, Detroit, and Philadelphia. Throughout the book, particularly in the opening chapter, MacLeod details his notion of “scenes” and their importance, separately and as a whole. For MacLeod, a “scene” is not like a scene on television or in a movie, which, he asserts, is essentially a perfected moment in time hermetically sealed for eternity. Rather, a “scene” for his purposes can be thought of more as an environment, or a petri dish out of which can arise all manner of musical experimentation. The scenes can be completely independent of each other or linked somehow. Indeed, as they evolve organically, they morph from independent to connected and back again as quickly as aspiring musicians can start a new band or record label. Where and how musicians and music lovers gather to create and experience “scenes” is, for MacLeod, as important as the “scenes” themselves. Edison's original recording studio in Menlo Park, the suburbs and clubs around Jersey City in the 1920s, neighborhood venues in Newark and Trenton in the 1950s and 1960s (especially as seen on local television shows like Disco Teen), the rise and fall of Ashland Park as a haven for those escaping disco in the 1970s, and the emerging independent music scene in Hoboken today all played a part in building New Jersey's musical heritage. MacLeod asserts that, unbeknownst to most music fans today, the whole of recorded music in the United States, and by extension the world, originated in a small studio attached to Edison's original research lab. He expertly relates how Edison laid down ironclad rules as to what types of music would, and would not, be recorded. For instance, Edison favored opera and what we today think of as classical music, as well as spoken-word poetry. In fact, Edison's unwillingness to record anything that clashed with his personal taste eventually led to the establishment of the first “scenes” outside his control. These included progenitors of what we think of as rhythm and blues as played in New York and Chicago speakeasys, Dixieland in New Orleans, and the beginnings of commercial country music by way of the Bristol sessions. Mind you, once it “began,” popular music flourished in New Jersey whether or not Edison had any part in it. In clubs that were often only semi-legal and sometimes were segregated and sometimes were not, musicians of every sort coalesced and diverged, laying the foundation for much of what we enjoy today. At every turn, in every chapter, MacLeod expertly provides a clear, if meandering, path from early grand opera singers whose names have largely been forgotten, to Thelonious Monk, The Ramones, Bruce Springsteen, and numerous lesser-known, but equally influential, bands. The rise and demise of local radio and television stations in various parts of New Jersey and the “scenes” they fostered receive thought-provoking analysis throughout the book. Little-known New Jersey-based connections to famous music festivals such as Monterey and Woodstock emphasize New Jersey's importance to popular culture. Equally obscure connections to “Surf Music” and “the Bakersfield Sound” will likely intrigue and delight fans of those “scenes” as well. Perhaps the only major New Jersey musical figure not profiled in detail in the book is 1980s country music superstar Eddie Rabbit. This may leave some readers hoping that a separate study will eventually fill in this and any other gaps. Some may initially wonder if Making the Scene in the Garden State: Popular Music in New Jersey From Edison to Springsteen and Beyond has much to offer music and popular culture lovers outside of New Jersey. However, a few moments spent reading a paragraph or two will reveal that the book is an engrossing read for anyone interested in the development of popular media, popular music, and American society as a whole.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".