BetterHomesTO, research instruments, codes, and final report
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
<b>Includes: </b>BetterHomesTO Codes & Themes developed through reflexive thematic analysis<b><br></b>Conversational surveysDocument ReviewOnline survey resultsReport with findings<br> <b>Methods:</b> document review, conversational surveys featuring closed and open questions (transcribed), online survey, participant observation of meetings<br> <b>Reflexive Thematic Analytical Approach:</b> an initial set of primary, <i>semantic</i> codes were drawn from the literature review and aligned with the evaluation framework principles and criteria. Through co-production with study participants, a set of secondary codes emerged. In this phase, I hard-copy coded the entire dataset, then collated the codes and relevant data extracts in preparation for later stages of analysis (See Braun et al, 2019).<br> <b>Ethics:</b> The research detailed here was conducted with human subjects, approval for which was granted by the University of Toronto’s Research and Ethics Board (REB) per protocol no. 00037210
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.512 | 0.002 |
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