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.
Bibliographic record
Abstract
The influences of science and technology on society and the environment (STSE) have \nbeen an integral component of the formal educational curricula for four decades, and yet \nindustrialized countries frequently struggle to balance the benefits of science and technology \nwith the social justice and environmental issues inherent to contemporary society. Canadian \ncitizens often fail to connect scientific and technological understandings with the subtle and yet \nubiquitous personal, political, cultural, environmental, and social consequences that result from \nthese understandings. This phenomenological research will explore potential discourses of \ncontrol within education and society that may preclude authentic, contextual, and meaningful \nunderstandings of science and technology relative to their significant consequences, and an \nimaginative adaptation of Egan's Ironic Understanding and McGinn's Foreground and \nBackground Dimensions to imaginatively express an awareness of postmodern STSE \nunderstandings. This research is designed to explore student understandings of how the diverse \nand complex influences of science and technology affect students through postmodern, \nimaginative, and constructivist photography. Participants demonstrated a limited Ironic \nUnderstanding of STSE, a critical awareness of specific modernist influences, increased personal \nand affective connections to science and technology, and an awareness of the duality of STSE. \nParticipants' photographic artifacts can be utilized to inform teaching and learning strategies in \norder to purposefully craft curriculum and lesson plan design for personalized and engaging \nlearning opportunities that incorporate students' awareness of STSE.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it