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Record W3045716051

Social enterprise in the UK: Models and trajectories

2019· book-chapter· en· W3045716051 on OpenAlexaff
Mike Aiken, Roger Spear, Fergus Lyon, Simon Teasdale, Richard Hazenberg, Mike Bull, Anna Kopec-Massey

Bibliographic record

Venuee-space (Manchester Metropolitan University) · 2019
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsImpact
Fundersnot available
KeywordsSocial enterpriseCorporate governanceContext (archaeology)Position (finance)NarrativePolitical scienceNeglectSocial policySocial positionPublic relationsEconomic systemBusinessSociologySocial changeEconomicsManagementGeographyLaw
DOInot available

Abstract

fetched live from OpenAlex

There is a growing interest in the social-enterprise (SE) arena in the United Kingdom but this term encompasses a highly diverse community of organisations. In the Anglo-Saxon context, these organisations have developed in different policy or business fields, with distinctive legal or governance models. They may also originate from very different historical periods. For example, some may be recent organisations set up with a specific SE focus and, in certain cases, with a strong business orientation – alternatively, there are organisations with deep roots in charitable or cooperative entities founded in previous centuries, and these origins continue to influence their aspirations and organisational models. Overall, the wide degree of variety and hybridity within the field has created difficulties in defining or counting UK social enterprises. In the last 20 years, policy makers have moved from a position of relative neglect of social enterprises towards taking a strong interest in their development. Hence, there have been new or amended legal identities, encouragement for these organisations to acquire physical assets or engage in the delivery of public sector services, and an endorsement at policy and practice level of the importance of these entrepreneurial organisations. It is also worth mentioning that social enterprises are more common in certain arenas of the economy (particularly in the field of human services) and less common in others (such as high-tech manufacturing), although there are exceptions. It is also important to indicate the nature of devolved powers to the constituent countries within the UK over the last 20 years. This has led to some divergent policies towards social enterprises being pursued in Northern Ireland, Scotland and Wales. For simplicity, the discussion here mainly refers to the English situation, unless stated otherwise.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0050.012
Scholarly communication0.0150.015
Open science0.0020.009
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.209
Teacher spread0.183 · 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 designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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