A Variety of Liberalism in Vancouver
Bibliographic record
Abstract
I opened this book with a poetic reflection on how I like to stand at English Bay, dreaming up alternative worlds. Perhaps the key problem with this scenario is that I am standing alone, entertaining fantasies, rather than taking action with others in the real world and waiting to see what we dream up together. In some sense, as we shall see in this chapter, my whimsical musing performatively realizes the intentions of some of the people who designed Vancouver. They built City Hall upon a hill outside of the downtown area from where it could appear to rule over the city without being particularly accessible (Monteyne 2010, 52). They offered very little space for public gatherings, where people might face either those in positions of power or one another to engage in dialogue. And they instead developed a thin, two-lane walkway around the red cedar-and Douglas fir-lined West End archipelago, encouraging people to turn outwards towards the sea; to literally turn their backs on the city. They wanted us to stand there, alone or in groups of two, whimsically musing about aquatic adventures. In this chapter I complicate the simplified picture of liberalism painted in Chapter 2, detailing the complex ways in which liberalism has and has not become embedded in the city my friends call home. The advantage of the critique I offered in Chapter 2 is that it gives us a broad overview of the history of liberal ideas and an outline of how these have become reality. But this same advantage is also a shortcoming. Such overviews end up assigning agentive force to a phantom. Liberalism becomes an ideology without real places or people. It is simultaneously the entire backdrop against which everybody operates and yet explains no single feature. It is the reason that society is crumbling around us and yet no individual person seems to fit the profile. With this shortcoming in mind, it is my contention that what is needed is a variety of liberalisms approach. This means recognizing that there are globally circulating ideas that have found their way into a range of institutions and individuals, producing similar results in seemingly disparate places, while also recognizing that liberalism is not merely a framework that is preconceived and imposed from above.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.031 | 0.027 |
| Scholarly communication | 0.017 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".