The Agonistic Politics of Invitation: Narrating Moments of Cultural Policy Interventions in Berlin, New York and Vancouver
Bibliographic record
Abstract
Abstract This paper offers the framework of an agonistic politics of invitation to nuance the political implications of contextually- and temporally-specific cultural policy invites that bring to light a range of conflicts. Invitations are conceptualized with respect to their rationale, form, role expectations, and responses in three empirical vignettes: (1) the collectivized articulation of Berlin’s trans-disciplinary Koalition der Freien Szene as future invitee in local cultural governance; (2) the counter-invitation formulated by New York City’s People’s Cultural Plan to tackle ongoing racial inequities in the municipal Cultural Plan; and (3) uninvited graffiti responses to Vancouver’s Chinatown public art call to reconcile century-long discrimination against Chinese Canadians. The paper argues that invitations crucially shape and condition future spaces of possibilities for collaborative urban cultural governance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".