Lesson Plan, Social Studies, 2nd Grade and 3rd Grade
Bibliographic record
Abstract
TEKS (Texas Essential Knowledge and Skills): History(C) explain how people and events have influenced local community history. (5) Geography. The student uses simple geographic tools such as maps and globes. The student is expected to: (A) interpret information on maps and globes using basic map elements such as title, orientation (north, south, east, west), and legend/map keys; and (B) create maps to show places and routes within the home, school, and community. (6) Geography. The student understands the locations and characteristics of places and regions in the community, state, and nation. The student is expected to: (A) identify major landforms and bodies of water, including each of the continents and each of the oceans, on maps and globes; (B) locate places of significance, including the local community, Texas, the state capital, the U.S. capital, major cities in Texas, the coast of Texas, Canada, Mexico, and the United States on maps and globes; and (C) examine information from various sources about places and regions. Lesson objective(s): TLW learn the local history of Port Isabel, TX. TLW learn the history of The Charles Champion Building. TLW be able to locate Port Isabel, TX and the Gulf of Mexico on a map Differentiation strategies to meet diverse learner needs: 1. Students can differentiate their own presentation. Teacher will offer choices. 2. Buddy system-students can work on project independently or with a buddy 3. Presenting ideas through both auditory and visual means
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.131 | 0.051 |
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".