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Record W7114889827 · doi:10.1215/00021482-11934651

The Immaculate Conception of Data: Agribusiness, Activists, and Their Shared Politics of the Future

2025· article· en· W7114889827 on OpenAlexaboutno aff

Bibliographic record

VenueAgricultural History · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAmerican History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyPoliticsArgumentativeParticipant observationSet (abstract data type)Interview

Abstract

fetched live from OpenAlex

This slim, critical, social science study uses ethnographic methods of participant observation and interviewing to explore the brave new world of big data in agriculture. Although it is not notably historical in its approach, this book may be of interest to agricultural historians who want to know more about recent developments at the intersection of food and agriculture with the data revolution. Its author, Kelly Bronson, is a science and technology studies scholar based in Ottawa, Canada, whose work draws on interviews and observations conducted from 2016 to 2018 in five Canadian provinces: Saskatchewan, Ontario, Quebec, New Brunswick, and Nova Scotia, but the issues are often framed more broadly, with little regard to place, as part of modern agricultural practice across North America, western Europe, and beyond.The text itself unfolds over five concise chapters and a mere 153 pages, which follow a clear argumentative path. First, a brief introductory chapter positions the work within the vast scholarly and public debates over data control and manipulation by Big Tech companies, such as Facebook and Google, outside of the agricultural sphere. The author makes a strong case for why agriculture should be a more central part of these debates, then proceeds in the second chapter to summarize the advent of big data within corporate-driven agricultural innovation, followed by a third chapter that identifies a similar set of concepts and ideas driving the ostensibly opposed set of activists for alternative, open-source agricultural innovation. She portrays, with considerable evidence, both groups as sharing a common set of assumptions around what she calls “the immaculate conception of data”—defined as “a vision that data are ‘raw’ and thereby provide truths about the world as it really is” (12)—that typically go unexamined and lead to the conclusion that big data serves as an unstoppable force in agriculture. The final two chapters offer a sustained critical examination of the hidden politics behind the immaculate conception of data, including how it operates in specific settings and how it can be “re-politicized” by recognizing all the pervasive human artifice and decision-making lurking behind big data that render it far from truly objective.As a work of critical data studies, this book is compelling and timely. There is not much historical depth, however, so further work by agricultural historians and historians of science and technology will be required to situate the recent changes in a longer-term trajectory. There are only fleeting references to historical examples, such as the technological promotion of Tench Coxe in the early US Treasury (15) and a brief comparison of two National Geographic articles from 1972 and 2016 that show a similar discourse around seed technologies and big data, respectively (48). Indeed, this reflects a chronological argument made repeatedly in the book: that big data is the third of three momentous technological shifts in agriculture, after chemicals and genetically modified seeds, all of which drove greater corporate control over farmers. Since the corporate turn toward control in data is relatively recent, this does not itself lead to historical analysis but rather to extended immersion in conferences, meetings, and field sites of present-day agriculture. As historians, we may wish to examine the deeper historical roots behind the immaculate conception of data, however, which certainly resonate with many earlier efforts, such as the early agricultural experiment station and extension movements, as well as disciplines invented to instruct farmers on what the data say they should do, such as “farm management” in the early twentieth century. Such work could build on Bronson's present-focused account, and this greater depth would need to acknowledge what is truly new and unprecedented about today's big data technology, much like those who point out the long history of plant breeding should not ignore what is qualitatively different about genetically modified seeds of recent decades.Bronson repeatedly stresses that a critical data studies approach is not intended as a frontal attack on big data, although there are plenty of examples that are likely to give readers pause, in which data further entrenches the power of Big Tech–oriented agricultural corporations. Instead, the discourse of “immaculate data” is interpreted as a conceptual and rhetorical resource, used without sufficient examination by a variety of participants, including activists challenging the dominant food system. If, as Greek economic thinker Yanis Varoufakis argues in his recent book, Technofeudalism (2023), we are entering a new era where power over data has ushered in a terminal transformation of capitalism as we know it, the data revolution may yet prove to be even more consequential than the earlier technological shifts in chemicals and seeds. As agricultural historians, we would do well to use this book as a springboard for launching our own investigations into the long-term history of this transformation, so that we can reveal the deeper antecedents and contexts of this profound shift.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.194
Teacher spread0.183 · 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 teacher head, not a consensus.

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

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
Published2025
Admission routes1
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