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Record W4396781950 · doi:10.1353/tech.2024.a926354

Hacking Diversity: The Politics of Inclusion in Open Technology Cultures by Christina Dunbar-Hester (review)

2024· article· en· W4396781950 on OpenAlexaboutno aff
Maria B. Garda

Bibliographic record

VenueTechnology and Culture · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsHackerDiversity (politics)Inclusion (mineral)PoliticsSociologyMedia studiesAnthropologyGender studiesPolitical scienceComputer scienceLawComputer security

Abstract

fetched live from OpenAlex

Reviewed by: Hacking Diversity: The Politics of Inclusion in Open Technology Cultures by Christina Dunbar-Hester Maria B. Garda (bio) Hacking Diversity: The Politics of Inclusion in Open Technology Cultures By Christina Dunbar-Hester. Princeton: Princeton University Press, 2020. Pp. 280. The open technology movement brought us the Linux operating system and the Firefox web browser. Its historical roots reach deep into the hacker and hobbyist cultures of the twentieth century. Hence, perhaps not surprisingly, open technology communities are facing the same problem as many other DIY cultures: lack of diversity. Since the 2000s, these issues have been challenged by a growing number of activists and social change advocates. Their volunteer work within open technology groups is the topic of Hacking Diversity, written by the leading scholar on democratic [End Page 740] control, Christina Dunbar-Hester. In her book, she poses a simple yet increasingly relevant question: "What happens when ordinary people try to define and tackle a large social problem?" (p. 3). In sociology, diversity reflects on the levels of inclusion of historically underrepresented groups in a social environment (e.g., workplace). Dunbar-Hester embraces diversity as an emic concept, "emanating from within the communities that form the subject of this study" (p. 17). There are arguably as many definitions of diversity as there are policymakers, but this kind of ethnographic approach allows the author to focus on the everyday practices of her respondents. Influenced by works of Gabriella Coleman (Hacker, Hoaxer, Whistleblower, Spy, 2015) and Sarah Davies (Hackerspaces, 2017), this book is a result of many years of extensive fieldwork and historical contextualization. Each of the six main chapters of Hacking Diversity introduces the reader to various examples of hacking, making, and crafting practices and communities. I especially applaud the attention paid to hobbyists from underrepresented demographic groups and borderline interventions, such as the experimental cryptodance event in Montreal that "conjoined arts practice with pedagogy about the principles of cryptography in computing" (p. 96). Dunbar-Hester directs much attention toward questions of social justice, and her observations are always framed with care and sensitivity toward the cultural complexity of the problem. The book is at its best when it critically investigates the relations of power in the open technology communities, be it online or in Brooklyn. To paraphrase the author, there is some deep irony in the fact that the previously discriminated social groups of geeks and nerds are now reproducing the dynamics of injustice within their own circles (p. 67). This kind of study will be of great value to future North American–oriented research, as it documents the diversity work within the hackerspaces at the time of the #MeToo and #BlackLivesMatter movements. Hacking Diversity exposes the internal struggles of a community that, on the one hand, has a lot of utopian faith in technological solutions being able to make the world a better place and, on the other, is slowly beginning to recognize that there is no simple hack that could solve the systemic problems society is facing. As Dunbar-Hester observes, just because the problem persists within technology culture doesn't mean it can be solved with a technological fix (p. 241). Furthermore, she makes a fine point that the diversity advocates in tech are often engaging with neoliberal and corporate-friendly notions of inclusion that are limited to representation politics and do not address the underlying issues of global equity (ch. 5). After all, if we investigate who works in the technology sector on a global scale, who actually makes the devices we all use, then "women workers of color actually abound" (p. 20). Overall, Hacking Diversity helps readers better understand the issues of diversity in the North American tech industry. It will prove to be a very useful resource for historians of technology, as it documents many ephemeral [End Page 741] events and communities. I hope the book will encourage more studies on local hacker culture, especially outside of the United States (such as Gerard Alberts and Ruth Oldenziel, eds., Hacking Europe, 2014), as well as on politics of inclusion in other areas of technology. Maria B. Garda Maria B. Garda is a postdoctoral researcher at the Centre of Excellence in Game Culture...

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.999
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.003

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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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.

Study designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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