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Record W3126709514 · doi:10.22215/etd/2017-12177

Impact of Research on Economics Professors’ Compensation

2017· dissertation· en· W3126709514 on OpenAlexaffabout
Adam Gadawski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsCarleton University
Fundersnot available
KeywordsSalaryCompensation (psychology)Quality (philosophy)InstitutionPolitical scienceEconomicsAccountingBusinessPsychologySocial psychologyLaw

Abstract

fetched live from OpenAlex

The purpose of this paper is to study the observable effects research quantity and quality have on the salary compensation a professor receives. This paper aims to assess which bibliometric variable best measures research, and how that research is rewarded through salary received. Other determinants of salary, as well as institutional conditions, will be analysed so that the structure of salary can be determined. The subject of study is tenured and tenure-track economics professors in Ontario for 2015. The results indicate that for the top professors, quality of research was rewarded. For most professors, research made modest contributions to salary, with the best measure of research incorporating both quantity and quality of publications. Years of experience was the largest determinant of salary. Whether a university was unionized or not had an impact on salary, while the research intensity of the institution was not significant.

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)0.005
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.416
GPT teacher head0.661
Teacher spread0.245 · 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
Published2017
Admission routes2
Has abstractyes

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