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Record W2787900149

Quantitative analysis component : on the determinants of innovation in services and its linkages with productivity

2017· article· en· W2787900149 on OpenAlex
Mario D. Tello

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.

fundA Canadian funder is recorded on the work.
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

VenueAmericanae (AECID Library) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Societies in the 21st Century
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsComponent (thermodynamics)ProductivityBusinessIndustrial organizationEconomicsRegional scienceEconomic growthGeography
DOInot available

Abstract

fetched live from OpenAlex

Analysis of services sector and innovation activities taken separately are scanty for Peruvian economy 1 and taken together not existent. The average share of real value added of the services sector out of GDP in Peru in the last decade has been about 40% (Banco Central de Reserva Del Peru, 2012) and the estimated employment share out of total occupied economic active population (OEAP) about 32%, wherein 77% of this employment comes from the informal sector. Most of the work on the services sector has been oriented to the analysis of export of services, in particular on the tourism sector (Tello, 2012b).

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.313
Teacher spread0.284 · 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