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Record W2593752916

WAGE DETERMINATES IN JORDANIAN LABOR MARKET COMPARATIVE STUDY (1976-2009)

2016· article· en· W2593752916 on OpenAlexvenueno aff
Hazem Alwadi, Firas Muhammad Al Rawashdi, Ibraheem Alshomaly

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicUnemployment and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsWageEconomicsWage growthLabour economicsFinancial sectorEfficiency wageAgricultureValue (mathematics)Wage shareFinancial marketFinance
DOInot available

Abstract

fetched live from OpenAlex

The study aimed to measure the degree of labor market regulation across business sectors in Jordan through identifying the mechanisms of wage growth determination for the period 1976-2009. Wage determinants in financial sector was less depending on output growth since to take considerable time for wages to adjust to output change unlike other sectors which respond more rapidly but on average with less value than financial sector . Wage and output time series in agricultural, construction, and all sectors were non stationary, this can be a sign of low regulation in these sectors. The financial sector seemed to be regulated since Wage and output time series were stationary and not cointegrated, which mean that wages in short run is not correlated on output and need more time to be. Finally we can say wages growth in Jordanian labor market was random and highly depended on output growth in less regulated markets (construction, agricultural, and whole labor market), while it depended more on ex-output factors in more regulated market (financial sector).

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
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 head0.038
GPT teacher head0.244
Teacher spread0.206 · 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.

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
Published2016
Admission routes1
Has abstractyes

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