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Innovation in the Absence of Principled Knowledge: The Case of the Wright Brothers

2009· article· en· W2078946154 on OpenAlexaff
Carl Bereiter

Bibliographic record

VenueCreativity and Innovation Management · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsWrightCompetitor analysisClosing (real estate)Product (mathematics)Unintended consequencesComputer scienceLaw and economicsSociologyManagementOperations researchEconomicsPolitical scienceLawEngineeringMathematics

Abstract

fetched live from OpenAlex

Although the Wright Brothers are most famous for achieving the first successful manned powered flight, their innovation that had a revolutionary effect on airplane design was a plane capable of making banked turns. Yet this appears to have been an unintended by‐product of their effort to maximize control, in contrast to the efforts of competitors to maximize stability. The success of the Wright Brothers in this effort can be attributed to their taking an approach that was on one hand well adapted to the low state of aeronautical knowledge existing at the time but that on the other hand was committed to the construction and pursuit of principled knowledge. This involved the use of analogies, not as a source of problem solutions but as an aid in developing theory‐like principles. It also involved sequences of increasingly realistic experiments. Their approach contrasts with that of J.P. Langley, who took what has become a traditional R&D or ‘theory‐into‐practice’ approach, dependent on a high level of principled knowledge. This history yields several suggestions, not radical in themselves, about how radical advances may be made in knowledge‐poor fields, which are still common today, especially in the human sciences.

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)0.025
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.018
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0200.061
Scholarly communication0.0130.016
Open science0.0020.010
Research integrity0.0140.013
Insufficient payload (model declined to judge)0.0040.001

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 head0.129
GPT teacher head0.428
Teacher spread0.299 · 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.

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

Citations25
Published2009
Admission routes1
Has abstractyes

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