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Record W4402109649 · doi:10.55016/ojs/jet.v44i1.52267

Capital, Power, and Habitus: How Does Bourdieu Speak to the Tenure Process in Universities?

2018· article· en· W4402109649 on OpenAlexaff
Carla DiGiorgio

Bibliographic record

VenueJournal of educational thought. · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsHabitusPower (physics)SociologyCapital (architecture)Process (computing)Cultural capitalSocial scienceComputer scienceArtVisual arts

Abstract

fetched live from OpenAlex

This paper uses sociologist Pierre Bourdieu's theory of social structure (1986, 1990a, 1990b, 1991 , 1995, 1998) to better understand the concept of tenure and the relationships that contribute to a conflicted experience for many. Social structures reproduce themselves according to the rules of the field, and various forms of social, cultural, and symbolic capital, underlined by economic capital. are traded by individuals who each have a sense of their value in the system, or habitus. Aspects of the tenure process reflect the rules of the field of academia, excluding those academics (Bonner, 2004; Connell & Savage, 2001). The process of tenure is subjective and can exclude those who are most worthy (Batterbury, 2008; Benton, 2007). A glut of professors can reinforce the status quo and challenge it (Bourdieu, 1988) . Recommendations are made to improve the inherent biases and conflicts within the process.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.305

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 communication0.0000.000
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 head0.009
GPT teacher head0.321
Teacher spread0.312 · 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 designQualitative
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

Citations4
Published2018
Admission routes1
Has abstractyes

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