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 city of Lawrence, Massachusetts, has a wonderful diversity, originally serving as a turn-of-the-century entry point for Irish, Polish, Italian, Syrian, and French-Canadian textile workers, and now attracting newcomers from the Dominican Republic, Puerto Rico, Vietnam, and dozens of other countries. Hispanics now make up almost 70% of the population (U.S. Census Bureau 2005). Like most cities, Lawrence faces significant challenges. A dwindling manufacturing base, and subsequent loss of manufacturing jobs, has created a city where over one-third of the population is below the poverty line. Unemployment, while declining from 15% in the 1990s, still remains at 10%, over twice the national average (EOLWD 2005). Lawrence schools face many of the same issues as other urban schools in the United States, including a reported dropout rate of 40% that is almost four times the reported state average (MDE 2006) and difficulties supporting and retaining highly qualified teachers. To address the issue of teacher retention, Lawrence has initiated a district-run program for all new teachers, pairing each of 60 new teachers with a mentor in their school who is teaching the same grade or subject area. Mentors meet regularly with the new teacher, observe him or her in class, and offer support and guidance. The intensive mentoring program costs the district $200,000 per year, a bargain compared to the $50,000 it can cost to recruit, hire, and train one new teacher. Six years ago, before the program was initiated, half of Lawrence's teachers left after their first year. Now, on average, 85% stay and 62% are still in the classroom after three years, which is 12% above the national average (Brady-Myerov 2007). The success of the local support program was recently discussed in a National Public Radio interview (Brady-Myerov 2007). In Lawrence, mentoring works. Many new teachers who leave schools after the first year report lack of support and poor working conditions as the primary reasons for leaving. New teachers can feel alone and vulnerable even working in a school building alongside scores of other teachers. At a time when many of our teachers are approaching retirement, and science and mathematics teachers are scarce, especially in urban settings, it is imperative that we support and retain teachers new to the profession. Thirty-three states now require school districts to have a teacher induction and mentoring program, but these programs vary in quality. …
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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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