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Record W6892558839 · doi:10.5255/ukda-sn-5388-1

Quarterly Labour Force Survey, December 2004 - February 2005: Local Area Data

2006· dataset· en· W6892558839 on OpenAlexaboutno aff

Bibliographic record

VenueUK Data Archive · 2006
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWelshQuarter (Canadian coin)Seasonal adjustmentSeasonalityLocal authorityData series

Abstract

fetched live from OpenAlex

The Labour Force Survey (LFS) has been carried out in the UK since 1973. From 1973 until 1983 the survey was carried out biennially, and from 1984 until 1991 it was conducted annually. In 1992 the quarterly LFS was introduced. For full background and methodological information users should refer to the main Quarterly Labour Force Survey (QLFS) series (held at the UK Data Archive (UKDA) under GN 33246). The Local Area Data series was produced quarterly alongside the main QLFS from 1992-2006, and included aggregated data on employment, economic activity and related subjects, covering Local Authority Districts (LADs), Training and Enterprise Councils (TECs), and their Scottish and Welsh equivalents. From 1992 until August 1997, the data covered Great Britain, and from September 1997 data from Northern Ireland were added. The Local Area Data were also available as an annual database between 1994-1995 and 1999-2000, for LADs at individual level, but these are no longer produced. LFS move from seasonal to calendar quarters In accordance with EU regulations, the LFS moved from seasonal (spring, summer, autumn, winter) quarters to calendar quarters (January-March, April-June, July-September, October-December) in 2006. The last seasonal Local Area Data dataset issued was the Quarterly Labour Force Survey, December 2005 - February, 2006: Local Area Data (SN 5392), and the first calendar quarter dataset was the Quarterly Labour Force Survey, January - March, 2006: Local Area Data (SN 5393). Users should note that there is some overlap between these two datasets. Further information on the seasonal to calendar quarter change and its impact on LFS data may be found in the following online article: Madouros, V. (2006) Impact of the switch from seasonal to calendar quarters in the Labour Force Survey, London: ONS. LFS Documentation The User Guides available with the UK Data Archive's LFS studies are those available at the time of deposit. Users can access the updated guides online via the ONS LFS User Guide pages.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.138
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.011
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.046

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 head0.050
GPT teacher head0.302
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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
Published2006
Admission routes1
Has abstractyes

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