Systemic ecological illiteracy? Shedding light on meaning as an act of thought in higher learning
Bibliographic record
Abstract
Research on ecological literacy often takes for granted that participants understand, and can construct the meaning within, the complex concepts involved, simply because they are able to use the appropriate terminology in a ‘fluent’ manner and/or can select the correct option on multiple choice tests. In this study, and in the larger two-year study it is part of, a trend has been unearthed regarding the ecological literacy of university students entering into a Bachelor of Education program. An analysis of the meaning contained in participant definitions has revealed that the vast majority of teacher candidates, graduates of many different universities, are unable to explain the meaning of key integrating ecological concepts at even a minimal level of maturity, alluding to a possible systemic problem. The findings, though preliminary, suggest that until we inquire into the meaning that teachers possess for key concepts rather than accepting fluent but shallow use of these concepts, we may be taking too much for granted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.040 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".