MétaCan
Menu
Back to cohort
Record W4386154495 · doi:10.18432/ari29646

Exploring the Textual and Tactile Weave of Academic Subjectivities:

2023· article· en· W4386154495 on OpenAlexaffvenue
Haley Toll, Cecile Badenhorst, Heather McLeod

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSubjectivityEmbodied cognitionSociologyAestheticsIndividualismNeoliberalism (international relations)PortraitIdeologySubjectificationEpistemologyVisual artsPolitical scienceSocial scienceLawArt

Abstract

fetched live from OpenAlex

Within the neoliberal university, academics become positioned around market-driven managerialist ideologies and the techniques enacting those principles. Audit cultures actively and continuously measure and shape academic subjectivities defined by a specific kind of success. The market-driven individualistic model can conflict with ethical ideals and longings for self-expression, while the mismatch between institutional goals and personal values creates an academic self that is pulled in conflicting directions. We become subjects of the discourse but we can limit our subjectivity and develop authentic insight. In this paper, we engage in a process of embodied making. We create textual and tactile self-portraits as a way of pushing back at neoliberal subjectivities, and to make visible our multiple selves. Although we recognize that we are always a part of what we resist, we use making as a way to create micro-resistances for our own renewal. Our self-portrait assemblages and stories are ambiguous and fluid but capture a view of selves hidden beneath the professional self. We are reminded that we are creative beings, and that there is room within neoliberalism to open intentional spaces. We may not always succeed in seeing our contradictory identities, yet we are able to occasionally capture glimpses of our shifting selves.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
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 head0.181
GPT teacher head0.349
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 designObservational
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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueArt/Research International A Transdisciplinary JournalSame topicManagement and Organizational StudiesFrench-language works237,207