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
In 2003, I conducted a qualitative study that examined the experiences of stakeholders connected to two community-based adult literacy programs. My 70 research participants belonged to seven stakeholder categories as follows: 37 learners (adult literacy students), 2 coordinators/instructors (head practitioners), 11 other staff (instructors and office support workers), 7 parents/significant others (learners' close relatives), 2 administrators (volunteer board members), 8 referral agents (government and community agency workers who refer learners to adult literacy programs), and 3 provincial funding agents (government employees responsible for adult literacy grants). In addition to program documents and long-answer questionnaires, the research data included 75 interviews with 58 individuals representing every stakeholder category Interviews were my richest source of information. They were also the most difficult and the most time consuming, totaling 68 hours of taped conversations, which took 584 hours to transcribe. This personal reflection uses my interviewing experiences as a means to prepare other qualitative researchers for the challenges, and the joys, of interviewing adult education stakeholders. My first challenge was to recruit program stakeholders who were willing to be interviewed. I was fortunate to have an enthusiastic provincial funding agent in my region of the province, and to have cooperative coordinators/instructors as key program informants. Not only did they actively recruit more individuals than I requested from their own programs, according to lists of respondent criteria that I provided, but they also recommended that I interview more than one provincial funding agent; they kindly provided names of agents who were most familiar with their programs. Therefore, instead of interviewing 35 stakeholders as indicated in my research proposal, I interviewed 58 altogether, each who added a new dimension to my understanding of their adult literacy programs. The support that I received from one provincial funding agent and from both coordinators/instructors was essential to my study's success. The first task of every qualitative researcher therefore should be to recruit key informants who endorse the project's means of data collection and who are committed to its research goals. I was afraid to ask respondents for permission to audiotape the interviews. I feared that they would refuse to speak in front of the microphone, or perhaps even seize the opportunity to back out of the study altogether. Thanks, I'm sure, to their preparatory conversations with their programs' coordinators/instructors, only one participant asked that I take handwritten notes instead of taping our conversation. He was a government employee referral agent whom I had expected to feel more comfortable with the interviewing process. Some respondents, of course, were reluctant to speak up at first, and a few others actually whispered throughout their interviews. Several lowered their voices or leaned way back in their chairs away from the microphone whenever they thought they might be making unpopular or unfavorable comments, and one learner periodically slipped papers over the microphone to muffle the conversation. Most respondents, however, were very cooperative and eager to have their stories heard. It is essential to reassure participants that the interviewer is the only person who will later listen to the tapes and that they will have an opportunity to review their transcripts and make any changes they wish. Given my position as a white, middle-aged female university employee, I expected that I would feel more comfortable conversing with some respondents than others and they with me. The interview guides gave me sets of questions to follow in a logical order, but I decided early in the interviewing process to engage in less formal conversations wherein I could gently probe for more detailed data and encourage respondents to share whatever information they wished to convey I therefore tried to find a common ground of experience or interest to ease into each interview, and then I let the conversation take its own course as we discussed the respondent's adult literacy program experiences. …
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 | 0.001 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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