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Record W3123846514 · doi:10.11575/sppp.v5i0.42396

Support for Business R&D in Budget 2012: Two Steps Forward and One Back

2012· article· en· W3123846514 on OpenAlexaff
John Lester

Bibliographic record

VenueRePEc: Research Papers in Economics · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInnovation Policy and R&D
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

The federal budget contains some sensible changes to the SR&ED investment tax credit, but the decision to reduce support for large firms to provide additional support for small firms is a step in the wrong direction. The Jenkins Panel expressed concern about excessive subsidization of small and medium-sized firms and recommended cutting back on the enhanced SR&ED credit in order to finance more targeted support for these firms. Following that advice would have improved the social return on support for R&D; in contrast, the budget measures marginally reduce the benefits to society from subsidizing R&D. The budget also announced $400 million in additional funding for risk capital. Returns in the venture capital industry are very low and the additional funding is unlikely to be successfully deployed until returns improve. There is abundant evidence that the tax credit for investment in Labour-Sponsored Venture Capital Corporations is crowding out private investment and contributing to low rates of return; eliminating the credit is therefore an essential first step in restoring the financial health of the venture capital industry.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.069
GPT teacher head0.321
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 teacher head, not a consensus.

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

Citations2
Published2012
Admission routes1
Has abstractyes

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