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Compensation Plan Implementation and Change: Consequences for Individuals, Teams, and Firms

2018· article· en· W2859807137 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAcademy of Management Proceedings · 2018
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsRemunerationCertificationCompensation (psychology)ManagementPolitical scienceSociologyLibrary sciencePsychologyComputer scienceEconomicsLawSocial psychology

Abstract

fetched live from OpenAlex

Implementing compensation plans is a vital human resource practice that affects individuals, teams, and organizations. However, compensation research remains neglected in management research. Specifically, little is known about the effects of implementing new compensation plans or changing existing plans. Understanding the response to changes in compensation is especially important under dynamic economic conditions. The papers in this symposium analyze rich field data and contribute to theory by examining the implementation of, and changes to, compensation plans and the effects on individuals, teams, and organizations. Impact of Changing Skill-based Pay Certification Criteria on Skill Proficiency Presenter: Eric Alan Surface; ALPS Insights Presenter: James Kemp Ellington; Appalachian State U. Presenter: Samantha A. Conroy; Colorado State U. Presenter: Reanna Harman; ALPS Solutions Presenter: Don Drewes; North Carolina State U. Presenter: Lauren Brandt; ALPS Solutions Presenter: Elisabeth Dezern; ALPS Insights Identity Work in Resolving the Paradox of Compensation System Implementation Presenter: Aino Tenhiälä; IE Business School Presenter: Saku Mantere; McGill U. Individual and Firm Response to the Remuneration Transparency Act in Germany Presenter: Spenser Essman; Darla Moore School of Business, U. of South Carolina Presenter: Anthony J. Nyberg; U. of South Carolina Presenter: Ingo Weller; LMU Munich Presenter: Julia Ebert; Ludwig Maximilian U. of Munich (LMU) Presenter: Lena Göbel; Ludwig Maximilian U. of Munich (LMU) Are Team Rewards Better than Other Pay Plans? A Meta-Analytic Investigation Presenter: Pingshu Li; UTRGV Presenter: Keshab Acharya; the U. of texas rio grande valley Presenter: Eduardo Millet; U. of Texas Rio Grande Valley Presenter: James P Guthrie; U. of Kansas Workplace Consequences of Competitive vs. Egalitarian Strategic Compensation Plans Presenter: Mahmut Bayazit; Sabanci U. Presenter: Dennis George Ma; U. of British Columbia Presenter: Danielle Van Jaarsveld; 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.098
GPT teacher head0.388
Teacher spread0.290 · 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