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Record W6977698753 · doi:10.64336/001c.81106

A generational perspective over the new commercial space age

2023· article· en· W6977698753 on OpenAlexaff

Bibliographic record

VenueJournal of High School Science · 2023
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsSpace AgeSpace (punctuation)Government (linguistics)Perspective (graphical)Space explorationOutreachSpace ShuttleField (mathematics)

Abstract

fetched live from OpenAlex

The prospects of growing commercial space exploration entities in a new space age have raised concerns among several scholars, who have debated its ethical, legal, and environmental implications. However, few studies in the outer space social survey field have attempted to examine public attitudes towards this subject. Additionally, such analysis has thus far not been conducted with a comparison across age groups. Past age group analysis, when applied to different disciplines of space exploration such as supporting increased NASA funding, indicated differing attitudes among those who have experienced different eras of the history of American space exploration (space race, space shuttle era, and the commercial space age). For this reason, this study combined past findings and applied them to a more futuristic perspective through a quantitative correlational research method. It was predicted that this study’s three age groups’ (generations one–three) perceived understanding of future commercial space exploration defined by commercial space activities (space tourism, space colonization, harvesting of raw materials in outer space, and commercial government partnerships) would be affected because of generational bias. The 268 surveyed participants indicated that the opinion aspect of an age group’s perceived understanding was affected but not their self-assumed prior knowledge. Key findings were the eldest group’s (generation one) tendency to align with commercial government partnerships and the youngest group’s (generation three) tendency to align opposite to generation one in support of more historically futuristic concepts. The research findings could be applied to the public outreach programs of government space exploration entities such as NASA.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.572
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.001
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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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