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Record W4213212007 · doi:10.1353/book.84171

Insurrectionary Infrastructures

2018· book· en· W4213212007 on OpenAlexaboutno aff
Jeff Shantz

Bibliographic record

VenuePunctum Books · 2018
Typebook
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessComputer scienceGeology

Abstract

fetched live from OpenAlex

Opponents of states and capital must be prepared to defend ourselves. To understand the nature of the state is to know that it will attack to kill when and where it feels a threat to its authority and power. But the struggles against exploitation, oppression, and repression must also move to the offensive.With the emboldening of reactionary forces on the far Right, there has been a renewed focus on issues of community self-defense, not only against the violence of the state but against organized fascists and Right-wing vigilantes alike. There has also been a developing seriousness, particularly among anarchist and antifascist, or antifa, activists.The goal of all anarchism is not to eliminate violence in social struggle (a futile and impossible pursuit given the nature of the state), but to limit the amount, degree, and extent of violence and harm inflicted by state agents, and their vigilante supporters, on the poor, oppressed, and exploited. And this is part of the emphasis on insurrectionary infrastructures. Non-material (emotional) and material resources and spaces are necessary to defend communities and workplaces under attack, but also to organize possible, and necessary, offensives.Insurrectionary Infrastructures reflects on strategies and tactics of rebellion and resistance and offers suggestions for fighting to win.TABLE OF CONTENTS // Chap. 1: Taking It Off the Streets: From Ritual to Resistance / Chap. 2: Anarchist Logistics: Sustaining Resistance beyond Activism and Insurrection / Chap. 3: I Want a Riot: Us versus Them on the Streets / Chap. 4: The Call for Insurrection / Chap. 5: To the Barricades? The Limited Infrastructure of the Streets / Chap. 6: Protect Ourselves: On the Necessity of Self-Defense / Chap. 7: Insurrectionary Infrastructures: Bases for Offense and DefenseABOUT THE AUTHORJeff Shantz is an anarchist writer, poet, photographer, artist, and activist who has decades of community organizing experience within social movements. He currently teaches critical theory and community advocacy at Kwantlen Polytechnic University in Metro Vancouver, Canada. Shantz is the author of numerous books, including Crisis States (punctum, 2016), Commonist Tendencies: Mutual Aid Beyond Communism (punctum, 2013), Green Syndicalism: An Alternative Red/Green Vision (Syracuse University Press, 2012), and Constructive Anarchy (Ashgate, 2010). Shantz is co-founder of the Critical Criminology Working Group and founding editor of the journal Radical Criminology. Some of his writings can be found at jeffshantz.ca. Follow him on Twitter @critcrim.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0080.007
Open science0.0020.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1050.023

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.

Opus teacher head0.011
GPT teacher head0.256
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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