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Record W4382394959 · doi:10.32920/23593656

Worry about professional education: Emotions and affect in the context of neoliberal change in postsecondary education

2023· preprint· en· W4382394959 on OpenAlexaboutno aff
Ken Moffatt, Sarah Todd, Lisa Barnoff, Jake Pyne, Melanie Panitch, Henry Parada, Sandy McLeod, Nataleah Hunter Young

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)Neoliberalism (international relations)Embodied cognitionWorryPower (physics)Emotion workContext (archaeology)IdeologyMeaning (existential)Social psychologyPsychologyCorporate governanceSociologyPolitical sciencePolitical economyPoliticsAnxietyManagementEpistemology

Abstract

fetched live from OpenAlex

A growing literature deals with the role of emotions and affect in making sense of how neoliberal changes in governance are experienced. In our study of the effects of neoliberal changes within Canadian universities, we discovered that faculty members are experiencing emotional as well as cognitive responses, to these changes. This paper aims to contribute to the understanding of how neoliberalism is embodied in emotion, shaping the spaces in which we are located. The ways in which neoliberal ideology reorganizes workplaces results in people experiencing a range of affects that are then displayed in the form of emotions. We consider how space shapes affect and, in turn, emotional responses to neoliberal change. These emotions generate meaning and work as a form of power that aligns bodies with, and separates them from, others (Ahmed, 2004a).

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.005
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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