Rethinking Overdetermination, Structural Power, and Social Change: A Critique of Gibson‐Graham, Resnick, and Wolff
Bibliographic record
Abstract
Working in the wake of theoretical tendencies that became prominent within geography during the 1980s, many studies of resistance have either bracketed or ignored structural power, with some versions of poststructuralism simply denying that structural power is a useful concept in a world where power is putatively highly fluid and dispersed. These sorts of approaches, exemplified by the recent works of J K Gibson‐Graham, Stephen A Resnick, and Richard D Wolff (GGRW), limit the ability of studies of resistance to articulate the conditions under which political and social struggles might transcend resistance and succeed in liberating groups of humans from the oppressive conditions against which they struggle. In this paper, I discuss issues surrounding analysis of structural power in the wake of poststructuralist critiques of “structural Marxism,” presenting an alternative to GGRW's interpretation of Louis Althusser's concept of “overdetermination.” Overdetermination is a crucial concept, because it is rightly seen as the key to a noneconomistic Marxism and has been championed as such by GGRW. I re‐examine the roots of Althusser's concept in the writings of Lenin and Mao, arguing for a way of reading overdetermination that is both noneconomistic and compatible with a notion of structural power.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.116 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".