The University as a Socio-Material Assemblage
Bibliographic record
Abstract
The objective of this thesis is to explore and subsequently develop the concept of the university as a socio-material assemblage with regard to three key concepts of assemblage theory: codes, territories, and globalization (different from the traditional views of globalization). The thesis does this building on a multimodal analysis of data gathered from 26 promotional YouTube videos from UK and Canadian universities. It introduces a new middle-range (mesolevel) theoretical framework by combining concepts from assemblage theory (AT) (DeLanda, 2006; Deleuze & Guattari, 2013), and the inquiry graphics approach (IG) (Lacković, 2020). The methodology focuses on exploring the meanings of the universities’ spaces, physical objects, actors (human and non-human), and the relationships among actors through inquiry graphics analytical lenses. It then establishes codes and territories based on the analysis that territorialize the university as an assemblage, as well as the decodifying and deterritorializing processes within it. Finally, it analyses the observed codes and territories through the lenses of homogenization and hybridization globalization theories. The thesis concludes that the university can be conceptualized and interpreted as a socio-material assemblage whose components are interrelated and have both material and social expressive roles. Further, codes and territories are defined by the strength of the links between their iconic and symbolic expressions. Each university assemblage is connected to other assemblages through the various multi-layered networks that each component belongs to, yet the interaction among the components of an assemblage is interpreted within its specific territories, codes, and semiotic systems. These in turn, are defined by applying the semiotic principles of the IG approach. Finally, the thesis makes three major contributions: it conceptualizes the university as a socio-material assemblage, it develops a middle-range theoretical framework by combining concepts from assemblage theory and the inquiry graphics approach that can be applied to understand other sociomaterial assemblages, and it explains the relation between globalization, territorialization and codification of universities as socio-material assemblages.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".