MétaCan
Menu
Back to cohort
Record W1530164559 · doi:10.1017/cbo9780511752049.013

Is macroeconomics for real?

2001· book-chapter· en· W1530164559 on OpenAlexaboutno aff
Kevin D. Hoover

Bibliographic record

VenueCambridge University Press eBooks · 2001
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsKeynesian economicsFront (military)EconomicsHistoryGeologyOceanography

Abstract

fetched live from OpenAlex

All are keeping a sharp look-out in front, but none suspects that the danger may be creeping up from behind. This shows how real the island was. J. M. Barrie, Peter Pan Children are often thought to be peculiarly honest – witness the story of “The Emperor's New Clothes.” My title comes from a group of my academic children: first-year graduate students. I teach a mandatory class in macroeconomic theory to graduate students in both an economics department and an agricultural economics department. The students in agricultural economics are typically more interested in crop patterns or natural resources – relentlessly microeconomic topics – than in unemployment, GDP growth, or interest rates. Each year at least one student, who I assume comes from the agricultural economics department, writes on the anonymous class evaluation something like this: “If macro- economics were real economics – which it is not! – this would have been a good class.” What is one to say to the honest and piercing doubts of an academic child? The idea that macroeconomics stands in need of a microfoundational base is a commonplace among economists. I shall argue that what motivates this belief are principally ontological concerns, naïvely, but pointedly expressed, in my students' questions about the reality of macroeconomics. I shall argue that ontological reduction of macro- economics to microeconomics is untenable. Thus, while the program of microfoundations may illuminate macroeconomics in various ways, it cannot succeed in its goal of replacing macroeconomics. To begin at the beginning, it might help to define the key terms. “Macroeconomics” is sometimes thought to be the economics of broad aggregates, and “microeconomics” the economics of individual economic actions.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.007
Scholarly communication0.0110.011
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0160.005

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 head0.043
GPT teacher head0.208
Teacher spread0.166 · 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 designTheoretical or conceptual
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

Citations12
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicGlobal Financial Crisis and PoliciesFrench-language works237,207