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Advancing Research on Identity Threat

2023· article· en· W4385216890 on OpenAlexaboutno aff
Christine D. Bataille, Heather C. Vough, Maïlys George, Achira Sedari Mudiyanselage, Pascale Fricke, Katja Wehrle, Mari Kira, Ute‐Christine Klehe, Haoying Xu, Harshad Girish Puranik, Danielle Van Jaarsveld, David Douglas Walker, Lingtao Yu, David Sluss

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)PsychologyPolitical sciencePhilosophyAesthetics

Abstract

fetched live from OpenAlex

The purpose of this symposium is to provide an assessment of the current state of the identity threat literature as well as introduce new streams of research that are advancing this literature. The four papers bring together authors from Canada, France, Germany and the United States and include a literature review, a conceptual piece and two empirical studies - one qualitative and one quantitative. Identity Threat under Scrutiny: A Review and Future Research Agenda Author: Mailys George; EDHEC Business School Author: Heather Ciara Vough; George Mason U. Author: Christine Deborah Bataille; Ithaca College Am I Next? Vicarious Identity Threat Through Observed Workplace Interactions Author: Achira Sedari Mudiyanselage; U. of Cincinnati Author: Haoying Xu; Stevens Institute of Technology Author: Harshad Girish Puranik; U. of Illinois at Chicago Identity Threats, Threat Emotions, and Identity Work Among Workers Suffering From Post-COVID Author: Katja Wehrle; Justus-Liebig U. Giessen Author: Mari Kira; U. of Michigan Author: Ute-Christine Klehe; Justus-Liebig U. Giessen Introducing Expressed Occupationalism and Considering its Identity Implications Author: Pascale Fricke; U. of British Columbia Author: Danielle Van Jaarsveld; U. of British Columbia Author: David Douglas Walker; U. of British Columbia Author: Lingtao Yu; U. of British Columbia

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.496
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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 head0.125
GPT teacher head0.463
Teacher spread0.339 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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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