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Record W2509627097

Deconstructing STEM: A Reading Through The Postmodern Condition

2016· article· en· W2509627097 on OpenAlex
Majd Zouda

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal for Activist Science and Technology Education · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerformativityCurriculumSociologyCompetition (biology)PostmodernismFace (sociological concept)Engineering ethicsPedagogyEpistemologySocial scienceEngineeringGender studies
DOInot available

Abstract

fetched live from OpenAlex

Since the beginning of the new millennium, educational research and policy making have increasingly involved integration of science, technology, engineering and mathematics (i.e. STEM). Integration of the four disciplines is argued to provide students with contextualized learning experiences that resemble real-life work in STEM fields, along with solutions to interdisciplinary problems that human face. In the U.S., the STEM movement has been boosted by global economic-based competition and associated fears, in terms of STEM graduates, when compared with other nations. However, many critiques question the nature and goals of this competition, as well as, the possibilities to improve STEM talents through the current conceptualizations and practices of STEM education. Through Lyotard’s (1984) conceptions of knowledge in the postmodern society, this paper analyzes some aspects of the STEM educational movement. It explores the construction of STEM discourse within competitive frames that place prime value on high performativity. There seem to be two characteristics of current STEM education that support performativity; these are an increased focus on technological and engineering designs, and a tendency for interdisciplinary education/curriculum integration. At the same time, the eagerness for performativity and competition seems to drag STEM education into selectiveness, thereby jeopardizing its possible benefits. Recommendations for educators are finally discussed.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.064
GPT teacher head0.455
Teacher spread0.391 · 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