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Record W2028366685 · doi:10.1515/1475-3693.1398

Increasing Share of Agriculture in Employment in the Time of Crisis: Puzzle or Not?

2012· article· en· W2028366685 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

VenueReview of Middle East Economics and Finance · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureProductivityEconomicsQuarter (Canadian coin)Subsistence agricultureLabour economicsAgricultural productivityConstraint (computer-aided design)Agricultural economicsDemographic economicsMacroeconomicsGeography

Abstract

fetched live from OpenAlex

In the first quarter of 2008, along with the beginning of the crisis, the employment share of agriculture in Turkey deviated from its long-run trend and started to rise. Both the timing and the direction of the change caused a public debate seeking an explanation of this phenomenon. Getting attention in the debate is the fact that labor productivity in agriculture has been declining since that quarter. How much of the increase in agricultural employment can be explained by the secular changes in its productivity? To answer this question, we use a multi-sector general equilibrium model in which employment share in agriculture is determined solely by the subsistence constraint and labor productivity in agriculture, where sectoral productivity growth rates are treated as exogenous. The model accounts for more than 90 percent of the decline in the agricultural employment share between 2000:Q2 and 2010:Q3. The model is also able to generate the increase in agricultural employment since 2008:Q1, although it slightly overpredicts the agricultural employment share. The model also predicts the sectoral allocations of labor in non-agricultural activities during the sample period. A detailed analysis of the driving forces of the growth in agricultural productivity is needed, since it lies at the heart of the secular changes in employment shares in Turkey.

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 score0.676
Threshold uncertainty score0.106

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 head0.042
GPT teacher head0.233
Teacher spread0.191 · 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