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Record W7033305315

Principles of Microeconomics

2017· other· en· W7033305315 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2017
Typeother
Languageen
FieldArts and Humanities
TopicMedieval and Classical Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsSimple (philosophy)Adaptation (eye)Key (lock)Sequence (biology)Complete information
DOInot available

Abstract

fetched live from OpenAlex

Principles of Microeconomics is an adaptation of the textbook, Microeconomics: Markets, Methods, and Models by D. Curtis and I. Irvine, which provides concise yet complete coverage of introductory microeconomic theory, application and policy in a Canadian and global environment. This adaptation employs methods that use equations sparingly and do not utilize calculus. The key issues in most chapters are analyzed by introducing a numerical example or case study at the outset. Students are introduced immediately to the practice of taking a data set, examining it numerically, plotting it, and again analyzing the material in that form. The end-of-chapter problems involve numerical and graphical analysis, and a small number of problems in each chapter involve solving simple linear equations (intersecting straight lines). However, a sufficient number of questions is provided for the student to test understanding of the material without working through that subset of questions. This textbook is intended for a one-semester course, and can be used in a two-semester sequence with the companion textbook, Principles of Macroeconomics . The three introductory chapters are common to both textbooks. This book has an editable web page on Open Library .

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.568
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.5750.008

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 head0.018
GPT teacher head0.189
Teacher spread0.171 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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