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Record W2884869979

The Employment Situation, September

2007· article· en· W2884869979 on OpenAlexaboutno aff
Murat Tasci, Michael Shenk

Bibliographic record

VenueEconomic Trends · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsNonfarm payrollsQuarter (Canadian coin)PayrollDemographic economicsJob lossEarningsLabour economicsEconomicsDemographyGeographyUnemploymentEconomic growthAgricultureSociologyFinanceManagement
DOInot available

Abstract

fetched live from OpenAlex

Nonfarm payrolls increased by 110,000 net jobs in September, the highest net increase since May 2007. This increase was within expectations. It is still below the average increase of 122,000 jobs per month in 2007. The Bureau of Labor Statistics (BLS) also revised its August payroll numbers significantly, reporting a job gain of 89,000 instead of a 4,000 job loss. The major reason for the difference that local figures for local education services were revised significantly; an increase of 39,000 was the final number, instead of a 31,000 decline as initially reported. We pointed out the erratic behavior of employment in local education services and suggested that it might be the reason behind the anomaly in the initial report last month. September’s job gains along with the revision for August imply an average monthly increase in payrolls of 97,300 in the third quarter of 2007—the lowest average monthly increase in a quarter since the third quarter of 2003.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.034
GPT teacher head0.373
Teacher spread0.338 · 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
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
Published2007
Admission routes1
Has abstractyes

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