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Understanding Change in Academic Knowledge Production in a Neoliberal Era

2014· book-chapter· en· W2249339554 on OpenAlexaboutno aff
Mathieu Albert, Wendy McGuire

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge productionProduction (economics)Political scienceKnowledge managementComputer scienceEconomics

Abstract

fetched live from OpenAlex

Abstract In this paper, we present and apply a new framework – the Poles of Production for Producers/Poles of Production for Users (PFP/PFU) model – to empirically study how one particular group of academic scientists has responded to neoliberal changes in science policy and funding in Canada. The data we use are from a qualitative case study of 20 basic health scientists affiliated with a research-intensive university in a large Canadian city. We use the PFP/PFU model to explore the symbolic strategies (the vision of scientific quality) and practical strategies (the acquisition of funding and production of knowledge outputs) scientists adopt to maintain or advance their own position of power in the scientific field. We also compare similarities and differences among scientists trained before and after the rise of neoliberal policy. The PFP/PFU model allows us to see how these individual strategies cumulatively contribute to the construction of dominant and alternate modes of knowledge production. We argue that the alignments and misalignments between quality vision and practice that scientists in this study experienced reflect the symbolic struggles that are occurring among scientists, and between the scientific and political field, over two competing logics and reward systems (PFP/PFU).

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.881
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.205
GPT teacher head0.373
Teacher spread0.168 · 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
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

Citations9
Published2014
Admission routes1
Has abstractyes

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