MétaCan
Menu
Back to cohort
Record W4321448300 · doi:10.21428/f1f23564.db5a6abe

Making the Most of the ‘Crisortunity’: Multidisciplinary Provocations on Techno-fixes and Precarity

2022· article· en· W4321448300 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIDEAH · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrecarityMultidisciplinary approachPolitical scienceSociologyGender studiesSocial science

Abstract

fetched live from OpenAlex

Provocations on Techno-xes and Precarity 2What does a robust and useful technological response to a crisis, aware and attentive to the biases and messages of digital media, look like?This paper responds to provocations and questions posed during our panel, Emergent-cy: Critical Digital Humanities in the Time of COVID at the Digital Humanities Summer Institute 2021 Conference & Colloquium, by attendees who particularly responded to the notion of "crisortunity" raised by Arun Jacob during the panel.This paper centres on crisortunity, a neologism coined by the cartoon The Simpsons in episode 11 of season 6 ("Fear") and since expanded upon by scholars like Tanner Mirrlees, within our different disciplines ("Ghoulish").Crisortunity-a crisis situation that also presents the opportunity for someone to gain something in return-unifies our offerings to the digital humanities.While contributors to this paper come from a range of fields-museum studies, journalism studies, media studies, and research creation-our responses are linked by an attentiveness to the uneven precarities and vulnerabilities so often symptomatic of institutional responses to crises, as well as the production, circulation, and management of information.Building on critical work that explores the ways that technologies from electronic monitoring of those serving parole or awaiting trial (Benjamin) to electronic benefits transfer systems in the United States social service system (Eubanks) are mobilized to fix social problems, we argue that techno-fixes often fail to fix; instead, they reinstate unequal and inequitable relations in the name of repair.In contrast, when communities organize to respond to crises on their own, tensions may arise between attempts for selforganization and anti-capitalist modes of creating and community.This paper thus explores the implications of qualifying something as a "crisis" with a discrete beginning and end, and what it might mean to offer fixes to something that is broken rather than curating, managing, repairing, or caring for something that is not yet irreparable (Gál).By leveraging this concept across our four disciplines, we hope to explore the various uses of terming something a "crisis."While in the present context, the term crisis might bring to mind the ongoing COVID-19 pandemic, crises can be financial, institutional, and/or architectural.For whom do crises toll?And for whom are they not crises at all, but opportunities to further leverage power, influence, and resources in the name of protecting investments?As we explore, care infrastructures are often depleted in favour of technofixes and precarious labour that continue, rather than break from, pre-crisis power structures and institutional modes.In our first section, Haley Bryant tackles the question of remediation during the COVID-19 pandemic in the museum field, where an accelerated focus on digital solutions warns of an increasing reliance on precarious labour and compromised practices of museological care.In the following section, Nelanthi Hewa examines how Substack and other newsletter platforms have positioned themselves as the saviours of journalism to ask whose crisis is solved, and whose is extended, when journalism is platformed.Camille Intson reflects on a research creation endeavour and international digital media gallery entitled Intermissions: Works for a New World, which emerged in response to the pandemic's impact on art and culture.In the final section, Arun Jacob discusses the infrastructural politics of the inherent techno-solutionism in crisis architecture.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.044
GPT teacher head0.310
Teacher spread0.267 · 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