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Record W7105676123 · doi:10.17605/osf.io/eywxn

The Instrumental Self: Proactive Self-Objectification as a Strategy for Work Vigor in the AI Era

2025· other· W7105676123 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDehumanizationValue (mathematics)Work (physics)Organizational behaviorCoping (psychology)Accommodation

Abstract

fetched live from OpenAlex

This study integrates Weber's Instrumental vs. Value Rationality, Piaget's Assimilation vs. Accommodation Theory, and The Extended Self Theory (Belk, 1988, 2013). We posit that AI-induced dehumanization pressure (Kim & McGill, 2024) compels employees to adopt Proactive Self-Objectification (PSO), an instrumentally rational (Weber) and assimilative (Piaget) coping strategy. PSO facilitates Functional Self-Extension (FSE)—the incorporation of AI's functional attributes into the self-concept—thereby yielding immediate gains in Work Vigor and Super-Agency. Crucially, this instrumentally-driven path systematically suppresses the relational and learning dimensions required by Value Rationality, leading to the decay of organizational resilience, specifically Learning Loss and Psychological Disengagement.

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)0.018
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.021
Science and technology studies0.0070.004
Scholarly communication0.0190.003
Open science0.0260.003
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0020.005

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 head0.025
GPT teacher head0.367
Teacher spread0.343 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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