Affective Orientations: Space, Temporality, and Virtuality in Queering the Map
Bibliographic record
Abstract
Launched in 2017, the website Queering the Map has since become what Ann Cvetkovich calls “an archive of feelings”. Using a Google Maps interface, the website invites its users to record their queer moments and experiences enclosed in black pins on the pink map. Navigating through this landscape of queer memories conjures up a powerful feeling of presence enabled by the anonymous bodies which inhabited a particular corner of the world in nondescript time. As such, Queering the Map assembles a “virtual” archive both in the sense that it is hosted on a digital network, and that it is a product of and at the same time produces queer time. Using “virtuality” as a conceptual point of connection, this paper looks at the ways in which Queering the Map brings together discussions of spatial production, networked affect, and queer temporality. Specifically, I see virtuality not as a characteristic of a technological apparatus itself, but rather as a set of emergent possibilities that lie with the affective experiences of its users. While the term “virtual” is frequently associated with digital media (as in “virtual reality”), scholars including Oliver Grau and Anne Friedberg have pointed towards longer lineages of artistic practices that can be thought of as virtual. In a similar effort to expand the concept of the virtual, Thomas Elsaesser has suggested that virtuality be understood as the conditional and the contingent, a modality not exclusive to digital media. Along these lines of thinking, I am interested in how the “virtuality” of Queering the Map connects seemingly disparate discourses on mapping, cyberspace, and queer affect. By examining conceptualizations of the virtual as a set of emergent potentials in these theoretical contexts, I show that new media do not so much produce virtuality as they reveal it. Following Sara Ahmed who poses the orientation in “sexual orientation” as a phenomenological question about how bodies are situated in space and grapple towards certain objects, I suggest that users’ navigation of a digital network like Queering the Map is intimately connected with their subjective orientation in the queer archive. This way, the virtual serves as a conceptual bridge between (new) media studies and queer theory, bringing together on the one hand, how presence is mediated across space and time, and on the other, the affective potentials opened up by this newfound closeness to queer places, times, and bodies.
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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 | 0.001 |
| 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 | 0.000 |
| 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 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".