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Record W7099553426

PUB DATE 1996-00-00

2016· article· en· W7099553426 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsCensusIrishClothingPopulationCurrent Population SurveyAgricultureQuarter (Canadian coin)Clothing industry
DOInot available

Abstract

fetched live from OpenAlex

The Census of Population provides data on the structure of employment by occupation and industry for Ireland that are supplemented by the Labor Force Survey (LFS), which collects information on employment by occupation and industry. Expected strong growth in the Irish economy from 1993-98 should lead to a significant increase in employment. This increase will not be large enough to absorb the expected rapid rise in labor force participation. In terms of sectoral forecasts, decreases are expected in the agricultural, manufacturing, and clothing and textiles sectors; increases are expected in all other sectors. Different sectoral trends in employment and continuing change in the occupational structure of sectors mean the aggregate expected change in employment will differ across occupations. Significant increases are forecast for professional, associate professional and managerial, and proprietors occupations. Occupational groups expected to experience employment declines are agricultural workers, laborers and

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.112
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8880.899

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 head0.173
GPT teacher head0.507
Teacher spread0.334 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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