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Record W3125182210

Of Academics and Professionals: The Difference Is in the Pay

2014· article· en· W3125182210 on OpenAlexaboutno aff
Călin Vâlsan, Elena Druică

Bibliographic record

VenueManager · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsChinaOrder (exchange)Higher educationPolitical scienceVariety (cybernetics)EconomicsBusinessLawFinance
DOInot available

Abstract

fetched live from OpenAlex

1. IntroductionIn 2012, Philip Altbach, director of the Center for International Higher Education at Boston College edited a book of readings called Paying the Professoriate: A Global Comparison of Compensation and Contracts. The volume could not have come at a better moment. It provides an international comparison of salaries in twenty-eight countries, across a wide variety of universities. Some of the findings are enlightening, although not surprising. In lesser developed countries, such as Armenia, Russia, and China, academics earn a very low pay and are compelled to rely on moonlighting in order to significantly supplement their income. In some cases, salaries are so dismal that university professors need to more than double their pay just to make ends meet. Even in countries in which pay is relatively more substantial, academics hold a second job, such as consulting or even something totally unrelated to their academic credentials. Obviously there is a brain drain from countries such as India, China, Russia, and others to countries, such as Canada, the United States, Germany, Australia, and similar. But the most damming finding appears the fact that salaries in academia lag behind the pay received by other professionals, such as lawyers, medical doctors, counselors, psychologists, engineers, and architects. This appears true across the board, including developed countries. Even academics who teach and research in law, business, or engineering tend to be underpaid relative to those who actually practice law, business, or engineering.The authors of the volume on academic pay consider that the viability of the education systems is contingent on the ability to recruit talented and capable academics. It stands to reason that in order to produce high quality research and scholarly work, one has to rely on outstanding talent. In order to have competent and well-rounded graduates, able to function as engaged, productive, and responsible citizens, one has to ensure excellence in teaching. This obviously requires the and the brightest of academics.In Canada and the United States, business schools are already paying a market differential to attract professors to teach disciplines such as Finance, Accounting, Marketing, Management and Human Resources. Business professors are invariably paid more than they counterparts teaching English Literature, Philosophy, or History. In accounting, starting salaries for young and inexperienced assistant professors routinely edge above $100,000/year; yet, it is increasingly difficult to find qualified accounting graduates holding a doctorate and willing to engage in a career of teaching and research. Accountants can easily double this amount by taking a job with an accounting firm, or any other successful corporation.Philip Altbach seems to conclude that by underpaying university professors relative to other professionals, one is jeopardizing the health and viability of the higher education system as a whole. The entire analysis and discussion that leads towards this conclusion is predicated on the assumption that academia is yet another form of professional activity. This begs the question of whether academics are indeed professionals, and if their activity and pay should be compared to those of other professionals.This paper claims that academics are quite different from most professional categories, although they are many common characteristics. The desire to compare academic pay to those of other professionals is humanly understandable, yet trying to turn academics into regular professionals would have far-reaching consequences from a wider social perspective. Emphasizing monetary rewards at the expense of intrinsic drivers would most likely attract the best and the brightest, but it would also change the nature and structure of the academic output. The next section compares and contrasts the characteristics of universities and those of professional organizations. …

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)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.022
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0040.010
Scholarly communication0.0180.014
Open science0.0010.005
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0220.004

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 head0.063
GPT teacher head0.406
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; 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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