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Record W4385228565 · doi:10.5281/zenodo.8179297

Critical Accounting for the Hidden Costs of Knowledge Production

2023· paratext· en· W4385228565 on OpenAlexaff
Leslie C. L. Chan

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typeparatext
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsProduction (economics)Cost accountingComputer scienceAccountingRisk analysis (engineering)BusinessEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Keynote lecture at the Critical Perspective on Accounting Conference, Universida Nacional de Colombia 2023<br> https://fce.unal.edu.co/cpa2023/ Critical Accounting for the Invisible Costs of Knowledge Production A handful of Western-based for-profit conglomerates dominate the present-day global academic publishing industry. This state of affairs has led to a highly inequitable, exclusionary, exploitative, and opaque system, ultimately enclosing public knowledge by an immensely profitable publishing oligopoly. This is a familiar story we have been hearing for some time. And despite various calls for reform, most notably the Open Access movement, the position of the publishers remains deeply entrenched. In this talk, I tell a story of power, of how corporate publishers have transformed into self-appointed governance bodies over local, national, and global knowledge production. They achieve this by establishing norms, standards, and metrics that confer prestige and enforce compliance on researchers striving for advancement in an intensely commodified and competitive yet artificial "international" market, supported by the mantras of academic capitalism and the globalized knowledge economy. Taking advantage of the digital turn and network effects, corporate publishers have been building "full-stack" or end-to-end digital platforms, exerting their influence on all aspects of the knowledge life-cyle, or supply chain, from research to publication, data curation, knowledge circulation, and certification. By encoding their profit-driven norms and standards into the very infrastructure that researchers rely on, they wield significant power over academic labour in ways that often go unnoticed but come with real, though poorly recognized costs and harms. These include dependence, epistemic injustice, loss of rights to research, homogenization and reduction of bibliodiversity, and decontextualization of local knowledge systems and traditions. Through case studies of mergers and acquisitions, including Elsevier, Clarivate, Spring-Nature, and the knowledge cartel they formed, I illustrate how these publishers capitalize on the extraction, collection, and analysis of big data and researcher-generated data traces to create new markets and shape "values" in the form of predictive analytics that researchers and institutions seek to enhance their global rankings—another powerful tool of governance in private hands. Significantly, the design of these platforms carries colonial and structural biases, empowering the already "rich" in scholarly capital and institutional advantages while pushing the scholarly marginalized and diverse knowledge systems further toward the epistemic peripheries. Despite the potential of Open Access and Open Science to democratize and pluralize knowledge, uncritical market-based thinking has been easily co-opted by the corporate agenda, further exacerbating deep-seated structural inequities in knowledge production. In this regard, the calls for fair and transparent pricing for publishing services detract from the real crux of the problem: contestation over structural power and who has the authority to set the knowledge production agenda, which in turn dictates how government and institutional resources are distributed, and how academic labour are valued. Considering the many unsuccessful attempts to reclaim the knowledge commons and co-create open infrastructure, my talk concludes with a call for new imaginaries and narratives of open and pluriversal scholarship, including exploring new metrics and accounting paradigms to consider the neglected costs and values of academic knowledge production. This is crucial in acknowledging the hidden costs and promoting a more equitable, localized, and diverse knowledge ecosystem. I call for exploring fundamentally relational, globally interoperable, yet locally independent community-governed infrastructure as a potential solution to the current challenges. Alliance-making with diverse social movements beyond the university that share the common values and principles of care-full relationships and stewardship of our knowledge as a common resource is needed now.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.083
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.032

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 head0.090
GPT teacher head0.359
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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