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Record W7005045438

The place of public services

2017· article· en· W7005045438 on OpenAlexaboutno aff

Bibliographic record

VenueInsight (University of Cumbria) · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsAusterityPublic sectorPrivate sectorGoods and servicesGovernment (linguistics)Quarter (Canadian coin)Local governmentEconomic sectorPeck (Imperial)Accommodation
DOInot available

Abstract

fetched live from OpenAlex

Professor Frank Peck of the University of Cumbria’s Centre for Regional Economic Development writes for in-Cumbria on the big issues of the day and the data behind them. This month he asks if the unfashionable and squeezed public sector, which employs 60,000 in Cumbria, can be an engine of growth. Recent debates on the economy have included questions about public sector pay and the wisdom (or otherwise) of continued austerity policies. In the aftermath of the economic crisis of 2008, it has been unfashionable, perhaps, to consider public services as vehicles for regeneration. Attention has been diverted elsewhere in the search for local growth in the private sector (no stone unturned). Yet it remains the case that many people in Cumbria can directly attribute their economic wellbeing to employment in the delivery of public services, either directly via the state or indirectly through private providers and the voluntary sector. The health and social care sector alone accounts for 32,000 jobs in the county, 13.6% of the total. The health sector actually provides employment for more Cumbrian residents than either retailing or accommodation and food services. Add to this those employed in education, local government, emergency services and various functions of central government and the total employed sums to 60,000, representing around a quarter of all jobs in Cumbria. The wages and salaries paid generate considerable spend that contributes towards the support of many small and medium-sized businesses providing goods and services in the private sector, and stimulates a more buoyant housing market.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.180
Teacher spread0.154 · 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 designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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