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Record W2343734051 · doi:10.21153/ps2015vol1no2art500

Introduction: Personas at Work

2015· article· en· W2343734051 on OpenAlexaff
Katja Lee

Bibliographic record

VenuePersona Studies · 2015
Typearticle
Languageen
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPersonaIdentity (music)CraftAgency (philosophy)SociologyWork (physics)Function (biology)NegotiationSocial psychologyPublic relationsAestheticsPsychologyComputer sciencePolitical scienceEngineeringArtHuman–computer interactionSocial scienceVisual arts

Abstract

fetched live from OpenAlex

In this special issue we take up many of these threads in order to examine and to better understand the work persona as a public identity we mobilize and perform to manage the demands of our labour. In particular we are interested in work as a social condition that makes particular demands on us, and compels and inspires us to craft and perform particular identities. The ways in which our labour and our employers shape, influence, and discipline our constructions and performances of persona in work settings does not, however, negate our agency in this process: the negotiation and management of sometimes competing and contradictory roles, impulses, and desires can be a site of anxiety and friction but also of creativity. In this introduction to the issue, work personas are framed as necessary—perhaps even inevitable—identity performances that are a condition of work, working, and interacting with other workers. However, because the conditions of how, where, and why we labour and what constitutes “work” have changed significantly over time, so too have our strategies for producing and performing work identities. In our present moment, the work persona has explicitly and self-consciously entered the marketplace as a valuable commodity as both employers and employees become hyper-aware of the significance, function, and processes of image management. Moreover, the ways in which digital and social media have changed our work cultures now make it increasingly difficult to talk about and perform a work persona that is a distinct entity from personas performed in other contexts.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.013
Scholarly communication0.0140.011
Open science0.0020.005
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0330.009

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 head0.118
GPT teacher head0.309
Teacher spread0.191 · 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 designNot applicable
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

Citations8
Published2015
Admission routes1
Has abstractyes

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