Cultural roads and Itineraries : Concepts and cases
Bibliographic record
Abstract
Like many academic projects, this book results from a series of reflections \nthat converged over the years. At the time of this book’s conception, \nAurélie Lacassagne and Jonathan Paquette had been working together \nfor years on a number of collaborative projects—the most important of \nwhich related to “terroir” and cultural industries in Canada. As such, this \nproject evolved from a variety of fieldwork that took place throughout \nthe provinces of Ontario and Québec, wherein the place of roads became \nsalient. Roads were a way of narrating regions, of narrating identity; roads \nenabled the stories of Canadian terroir that had only very recently been \ncrafted. Roads, in a sense, provided spatial support for the implantation \nof terroir’s imaginary. Outside of this collaboration, roads have been an \nimportant part of Aurélie’s theoretical approach to French-Canadian and \nFrench-American literature. The importance of roads has also emerged \nin Jonathan’s fieldwork in Asia. In Hong Kong, heritage and nature trails \nare an important component of the local cultural scene. While Jonathan’s \nwork focuses on museums and heritage policies, roads revealed another \ndimension of heritage in Hong Kong. Similarly, Christophe Alcantara’s \nv \nvi Preface \nwork in communications and on the use of social media reached an interesting \nturning point when he took an interest in the representations of \nroads and selves on Instagram. Studying the social media practices of \nhundreds of Instagram users, Christophe’s work found patterns in the \npicture-taking practices of users’ that suggested their selfies were not as \nshallow as one might think; the roads portrayed in these images often \nrevealed a new sense of spirituality and depth to those who took the \npictures. \nThese different ideas and perspectives on roads converged in 2018, \nwhen we all met in Montréal for the Société Québécoise de science politique’s \nannual meeting. This was the occasion where many of the ideas \nthat are discussed in the pages of this book first took form. \nIt is with all of this in mind that this book aims to achieve two \nobjectives. First, the book aims to discuss roads from an interdisciplinary \nperspective; it unites ideas, concepts, and notions from a number \nof different disciplines: history, geography, economics, political science, \nliterature, philosophy, and many others. As such, the book engages with \nthe works of many important philosophers and social scientists—notably \nDeleuze, Bakhtin, Heidegger, Simmel, Castells, among many others. \nSecond, this book focuses on cultural roads, bringing us closer to disciplines \nthat have already engaged with the cultural dimensions of roads, \nitineraries, paths, or routes. Notably, tourism studies, heritage studies, \nleisure studies, and regional development have all contributed to frameworks \nand concepts that further the understanding of the cultural aspect \nof roads. Thus, this book engages with the rich work that has emerged \nin these disciplines since the early 2000s and with greater force since the \n2010s. The cases discussed in this book further the ongoing discussions \nand debates around the cultural aspect of roads; the cases we have selected \nand the approach we have privileged explore new concepts and test the \nboundaries of this object of study.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.027 | 0.054 |
| Scholarly communication | 0.025 | 0.018 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".