MétaCan
Menu
Back to cohort
Record W7099729056

2 How dark is the night: the consumers ’ mood coping with the crisis. Evidences from ISAE Consumer Survey Preliminary draft

2016· article· en· W7099729056 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsnot available
Fundersnot available
KeywordsConsumer confidence indexQuarter (Canadian coin)PopulationCoping (psychology)Economic indicatorFinancial crisisUnemploymentMood
DOInot available

Abstract

fetched live from OpenAlex

Since 2008 the global economy, following also the financial crisis, is facing a severe decline in economic activity and the economic estimates concerning the first quarter 2009 are even worse. While in the major industrialized economies Consumers Confidence Indicators (CCI) show common negative trends, in Italy we have observed a different pattern. After a sharp fall beginning in 2007, the CCI (in the Italian definition) is unexpectedly showing some signals of recovery since the end of summer 2008. Specifically, the confidence on the personal condition improved, while the economic picture was considered in deterioration at least till the first quarter of 2009. From another point of view, whereas the expectations on the future are worsening, the evaluation on present conditions are recovering. It seems that the effects of the financial crisis have not influenced Italian consumers yet, as it is documented worldwide. It is worth sorting out this puzzle. The paper tries to explain these trends starting from the role played by the single elements on which the composite indicator of confidence climate is determined. Then the recent price evolution and its influence on the Italian Consumer Confidence dynamics are investigated. Since end of summer 2008, the sharp inflation slowdown together with nominal wages increase, may have contributed to keep confidence from falling. A further tool for explaining recent CCI dynamics could also be represented by a micro-data analysis of opinions of population sub-groups, because some of these could have been more exposed than others to the crisis. Therefore the paper explores reactions of different consumers segments (e.g. by income, professional status, household composition).

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score0.666

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 studies0.0010.001
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.258
Teacher spread0.236 · 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 designNot applicable
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

Explore more

Same topicNuts composition and effectsFrench-language works237,207