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Record W3005469480 · doi:10.1177/1940844720968213

Venturing From Home: Writing (and Teaching) as Creative-Relational Inquiry for Alternative Educational Futures

2020· article· en· W3005469480 on OpenAlexaboutno aff
Anne Pirrie, Nini Fang

Bibliographic record

VenueInternational Review of Qualitative Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsFlourishingSociologyForegroundingThrivingEnvironmental ethicsPedagogySocial scienceSocial psychologyPsychology

Abstract

fetched live from OpenAlex

This article explores the ecology of contemporary higher education by foregrounding the ethical relation between its authors. The article expresses their commitment to throwing off familiar academic conventions in order to promote human flourishing in a sector that has been colonized by new managerialism and the associated mechanisms of “performance management,” surveillance, and exclusion. The authors write into the emblems of the naajavaarsuk (the ivory gull) and isumataq (the Inuit storyteller). They explore collaborative writing as an ethical, relational practice whilst exposing the lived problematics that have become the “new normal” in the contemporary academy, for instance, the fetishization of “student satisfaction.” The latter has gained traction in the UK in recent years, and in extreme cases can call forth acts of ethical violence that induce deep and long-lasting effects. Their account is visceral rather than abstract, rooted in lived experience and in theory. The authors conclude that the precondition for human flourishing in conditions of constraint is neither all-out resistance nor quietist acceptance of the status quo. It is to open up a space for education that inheres in our relation to the other, and quietly to resist being defined and limited by practices of monitoring and surveillance.

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)0.021
metaresearch head score (Gemma)0.023
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: none
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0090.061
Scholarly communication0.0200.018
Open science0.0030.011
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.545
GPT teacher head0.655
Teacher spread0.110 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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