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Record W7093932404

Prepreke i šanse na putu ka novom modelu privrednog razvoja i zapošljavanja

2012· article· W7093932404 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

VenueTechnoRep (University of Belgrade – Faculty of Technology and Metallurgy) · 2012
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicRegional Development and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentSerbianGovernment (linguistics)Economic analysisQuarter (Canadian coin)Unemployment rate
DOInot available

Abstract

fetched live from OpenAlex

Very negative economic trends in the Serbian economy are caused very negative economic effects, such as low rate of GDP, very big inflation, growth of debt, unemployment and reduce of the life standard. In this conditions Government of the Serbia does main directions of the economic development in the future ten years. In this paper analysis of the Serbian economic trends in the first year of the Model implementation are done, such as results in the first quarter of the 2012. It is concluded that forecast results are very optimistic and unreal, and in the real conditions are unreal. On the way of the new model of the economic development and employment it is suggested rational using of the domestic sources, it means human at the firs place, and to take the future economic development to expert team, which has competitions for solving economic problems in the future.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.033
GPT teacher head0.205
Teacher spread0.172 · 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