MétaCan
Menu
Back to cohort
Record W2613256403 · doi:10.1177/1035304617709659

Automotive surrender: The demise of industrial policy in the Australian vehicle industry

2017· article· en· W2613256403 on OpenAlexaff
Jim Stanford

Bibliographic record

VenueThe Economic and Labour Relations Review · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsMcMaster University
FundersAustralian Government
KeywordsAutomotive industryIndustrial policyDeregulationLiberalizationEconomicsInternational tradeBusinessMarket economyEconomyInternational economicsEconomic policyEngineering

Abstract

fetched live from OpenAlex

Abstract Australia developed a strong and successful automotive manufacturing industry after the Second World War, based on active industrial policy. But in 2017, mass vehicle assembly in the country will cease altogether, as the last global automakers operating in the country close their final plants, with negative spillover effects along the automotive manufacturing supply chain. After 2017, Australia will be the only major industrial country with no vehicle assembly whatsoever. This article analyses the shifts in industrial policy that explain both the initial postwar expansion, and the subsequent decline and closures. Policy-makers incorrectly assumed that the critical goal of stimulating automotive exports could be achieved through trade liberalisation, but dismantling tariffs only stimulated vehicle imports without increasing overseas demand for Australian cars. Production declined in tandem with tariffs, and there was no clear industry policy strategy for facilitating the redirection of released resources to more productive manufacturing activity, when that outcome, predicted in neoliberal comparative advantage theory, failed to materialise. Financial market deregulation, resulting in financialisation of the economy, coupled with high commodity prices, resulted in an overvalued and volatile currency, attracting foreign investors to resources and asset speculation while appearing to increase manufacturing production costs. A clear contrast is drawn between Australia’s policy passivity in recent decades, and the continued policy activism visible in other jurisdictions of all political orientations – including countries which, particularly after the global financial crisis, faced economic and industrial challenges at least as daunting as Australia’s. In the 1970s, Australia had been among the world’s top 10 auto manufacturers; after 2017, it will be one of only two G20 countries completely lacking mass automotive manufacturing capacity. The industry’s disappearance from Australia is shown to have resulted from some unique policy choices: understanding them may help avert future similar policy errors.

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)0.005
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0080.003
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.000

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 head0.061
GPT teacher head0.319
Teacher spread0.258 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Economic and Labour Relations ReviewSame topicGlobal trade, sustainability, and social impactFrench-language works237,207