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Record W2913636461 · doi:10.1080/01900692.2019.1575853

A Comparative Analysis of SME Friendly Public Procurement: Results from Canada, Hungary and Italy

2019· article· en· W2913636461 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Public Administration · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic Procurement and Policy
Canadian institutionsPublic Works and Government Services Canada
Fundersnot available
KeywordsProcurementEconomic shortageBusinessMarketingHuman resourcesEconomicsManagement

Abstract

fetched live from OpenAlex

This paper studies SMEs’ participation in public procurement in light of perceived barriers and expected benefits of accessing the public marketplace. It presents a comparative analysis of SMEs’ participation in three countries that share similar approaches to SME-friendly public procurement. A common survey protocol was developed to be administered to SMEs in the three countries. Data collected were then analysed using regression methods. Findings suggest that some issues that are typically considered critical barriers, namely administrative requirements and award based on lowest price do not hinder participation. However, findings also suggest that firms’ characteristics associated with size are still relevant hindrances, and that SMEs’ involvement are affected by a shortage of tangible (human and financial) and intangible resources (experience). These findings provide guidance to fine-tune public procurement policies directed to SMEs.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
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 head0.035
GPT teacher head0.284
Teacher spread0.249 · 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