Fiction as Pedagogy: Toward a De-Anthropocentric Architectural Education
Bibliographic record
Abstract
Critiquing the anthropocentric dispositions of architectural education, this dissertation introduces a "de-anthropocentric" vector of ethical thinking through fiction as a form of pedagogy.The term de-anthropocentric as opposed to non-anthropocentric here posits nonhuman life as an important dimension of architectural consideration while acknowledging that there are limitations to understanding or advocating on behalf of the nonhuman other.By problematizing anthropocentrism in this way, the research participates in concurrent discourses in philosophy, education theory, anthropology, biology and literature studies that challenge the inherited biases of Western ontology and epistemology.Recognizing the predominance of education in structuring these biases, the research takes inspiration from experimental approaches in posthuman education studies that historically situate and reorient definitions of the human and disciplinarity.Toward this, the dissertation investigates three trajectories in literature studies as departure points: the weird realism of Howard Phillips Lovecraft, the multispecies worlding of Donna Haraway and the graphic portrayal of animal subjectivities in David Herman's narratology beyond the human.From these examples, the dissertation theorizes nonhuman narrative, representation and worldbuilding approaches in an architectural context.Finally, locating the early Renaissance as a period of major educational transition in architecture, the research analyzes Antonio di Pietro Averlino's Libro architettonico (1461-63) as a model of fiction-based pedagogy for the present.Written as a iii continuous fictional dialogue disrupted by digressions into the natural environment, animals, anecdotes, fictional buildings and social practices, the work offers a multifaceted educational model for questioning human-nonhuman relations.Between text and image, the work instructs by imagining the ideal city of Sforzinda through the narrative device of the golden book: a source of ancient literary wisdom.Following an analysis of Filarete, the dissertation presents a re-interpretation of Filarete's golden book as a pedagogical device to channel critical insight from literature and other disciplines into architectural education.My sincerest appreciation goes to Stephen Fai for continually reminding me what this dissertation was trying to do and helping to achieve it.I am indebted to him for the many opportunities he has provided throughout my academic career.Claudio Sgarbi has been a source of deep insight and necessary interrogation throughout the years.I owe him immeasurable gratitude for his encouragement and for all the tunnels and burrows he has brought into my thinking and writing.Michael Jemtrud brought my attention to many of the discourses that inspired this dissertation.I truly appreciate his continued presence and willingness to listen to these ideas since my time at McGill.Roger Connah's pedagogical insight shaped my teaching and thinking tremendously during these past five years.Because of him I will be deschooling for many years to come.Lara Chow always found a way to keep me involved in interesting projects while abroad.Federica Goffi was a constant support throughout this degree.I owe profound gratitude and mil obrigados to Ana Tomé and Carlos Sardinha for their encouragement and support in the dark days of the pandemic.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.068 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".