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Record W4405488499 · doi:10.33137/cjal-rcbu.v10.43049

Reckoning with the Legacy of Land-Grant University Libraries, Archives, and Special Collections as Ventures of Pioneer Veneration

2024· article· en· W4405488499 on OpenAlexvenueaboutno aff
Dulce Kersting-Lark, Jylisa Kenyon, Marco Seiferle-Valencia

Bibliographic record

VenueCanadian Journal of Academic Librarianship · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
FundersAndrew W. Mellon Foundation
KeywordsVenerationLand grantLibrary sciencePolitical scienceGeographyArchaeologyComputer sciencePublic administration

Abstract

fetched live from OpenAlex

Land-grant colleges and universities in the United States, and by extension their libraries and archives, seek to uphold a three-part mission of teaching, research, and service, while also focusing on equality of access, regardless of class. The admirability of that mission, however, is tempered by “genesis amnesia,” where, as Pierre Bourdieu and Jean-Claude Passeron say, “societies cover up or erase the origins of policies or institutions in order to obfuscate the social constructions that underlie them.” Other former settler colonies, such as Canada, maintain similarly structured and afflicted colleges and universities. For many institutions, the terms “land-grant,” or in Canadian contexts “land-endowed” or “land-financed,” act as a veneer, covering up and at times venerating an extractive and traumatic process by which Indigenous peoples were dispossessed of their lands. In this reflective case study, we define pioneer veneration as a symptom of colonialism and describe recent efforts to challenge it within our own library and archives. Using two collections containing Indigenous knowledges but not (primarily) Indigenous belongings, we explore our attempts to challenge pioneer veneration and seek out more impactful and purposefully reparative avenues of service to Indigenous patrons and stakeholders. By specifically defining the term pioneer veneration and discussing our institution’s effort to counter it in two specific collections, we hope to expand the lens of the types of collections that can be part of decolonization work and offer some replicable examples of work that redresses white supremacy and colonialism in institutional archives.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0000.000
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 head0.026
GPT teacher head0.234
Teacher spread0.208 · 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 designTheoretical or conceptual
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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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