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Record W3121641876 · doi:10.1111/hequ.12305

The closed academy? Guild power and academic social class

2021· article· en· W3121641876 on OpenAlexaff
Bruce Macfarlane, Alison Elizabeth Jefferson

Bibliographic record

VenueHigher Education Quarterly · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsGuildPower (physics)Social capitalSymbolic powerSociologyClass (philosophy)PrestigeCultural capitalSymbolic capitalSocial sciencePolitical scienceLawEcology

Abstract

fetched live from OpenAlex

Abstract Academic inbreeding is a deeply ingrained practice which needs to be understood by reference to the medieval guilds. Drawing on the guild concept and associated benefits of forms of capital, a distinction is drawn between ‘guild‐route’ academics who have followed a privileged, linear path into academe and their ‘non‐guild’ counterparts who tend to enter later in their career from the professions or industry, often without a PhD. The tendency to represent early career researchers from a guild background as members of an academic proletariat is largely misleading and fails to take account of their privileged entrée into academe. Their experience is contrasted with those recruited via the non‐guild route who do not have the benefits of the valued social, cultural or symbolic capital needed to advance their careers. Policy implications are discussed to better understand the effects of academic social class on recruitment practices in universities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0140.029
Scholarly communication0.0110.005
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.001

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 head0.028
GPT teacher head0.356
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations29
Published2021
Admission routes1
Has abstractyes

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