1. Shaʻar ha-emunah. Shaʻar Erets Yiśraʼel. Shaʻar bet din. Shaʻar ha-geʼulah. Shaʻar derekh erets. Shaʻar ha-hashḳafah. Shaʻar ha-ḥesed. Shaʻar ha-musar. Shaʻar ha-moʻadim. Shaʻar ha-midot. Shaʻar ha-misṿot -- 2. Shaʻar ha-nevuʼah. Shaʻar ha-ʻavodah. Shaʻar ha-ʻaṿerot. Shaʻar ha-tsibur. Shaʻar ha-Torah. Shaʻar ha-talmid ḥakham. Shaʻar ha-teshuvah.

ʻInyene Orah ḥayim : ʻavodat H., tefilah, berakhot, Shabat, Rosh ha-shanah, Yom ha-kipurim, ḳiyum mitsṿot, teshuvah, ḥinukh -- ʻInyene Yoreh deʻah : Torah, tsedaḳah, ʻinyanim shonim, midot, biṭaḥon, yom huledet -- Heʻarot ʻal Talmud Yerushalmi -- Hosafot le-Sefer Derekh ʻavodato, Shaʻar ha-biṭaḥon -- Ḳunṭres Tsidḳat Ḥanah : ḥidushim ṿe-liḳuṭim ʻal hilkhot ḥag he-Pesaḥ ṿe-Hagadah shel Pesaḥ (Mahadurah 3) -- Ḳunṭres Tsemaḥ Yiśraʼel : ʻal ʻinyene minhagim (Mahadurah 2) -- Ḳunt̥res Ḥesed ṿe-emunah : heʻarot ṿe-ḥidushim ʻal Sefer ḥasidim (Mahadurah 2) -- (...) Ḳunṭres Mile di-hespeda : ʻal zeḳeni ha-r. he-ḥ. Rabi Shelomoh Ḥayim Haizler zatsal. (shrink)

ha-R. ha-ḳ. R. Mosheh mi-Drogiṭshin -- ha-R. ha-ḳ. R. Avraham me-Ulinov -- ha-R. ha-ḳ. R. Shelomoh Leyb mi-Lenṭshna -- ha-R. ha-ḳ. R. Meʼir mi-Primishla -- ha-R. ha-ḳ. R. Avraham mi-Miḳalyov -- ha-R. ha-ḳ. R. Daṿid mi-Zovliṭov -- ha-R. ha-ḳ. R. Shmelḳe mi-Sasov -- ha-R. ha-ḳ. R. Yeshaʻy. Shor -- ha-R. ha-ḳ. R. Yeḥiʼel Mikhal.

Ḳarnot tsadiḳ -- Liḳuṭe Eliyahu -- Minhage ḳ.ḳ. 'Bet Ya'aḳ ov' be-Ḥevron.

Avne Shelomoh -- Zikhron Shelomoh -- Daʻat Shelomoh.

ḥeleḳ 1. Oraḥ ḥayim. Mikhtavim -- ḥeleḳ 2. Hadrakhot be-ʻinyene Talmud-Torah ṿe-ḥinukh ... -- ḥeleḳ 3. Liḳuṭim, mikhtavim --.

[1] ʻAl ʻinyene ḥinukh ha-banim ṿeha-banot ṿi-yeme ha-baḥarut-- [2] ʻAl ʻinyene derekh ha-Ḥasidut lesayeaʻ le-zulato be-ruḥaniyut ṿe-nilṿeh elaṿ mikhteve ḳodesh be-ʻinyan zeh.

A powerful feature of global health research is data‐sharing with regions which bear the heaviest burden of disease. It offers novel opportunities for aggregating data to address critical global health challenges in ways higher than relying on individual studies. Yet there exist important stratifiers of the capacity to share data, particularly across the Global North‐South divide. Systemic challenges that characterize sub‐Saharan Africa and disadvantage the region's scientific productivity threaten the burgeoning data‐sharing culture too. Like all endeavors requiring equal commitments under (...) unequal circumstances, a strong ethical impetus is needed to help reduce inequities and imbalances to encourage adherence. This article discusses mandatory data‐sharing in relation to peculiar challenges faced by sub‐Saharan African scientists to suggest ethical principles for rethinking and reframing solutions. We propose six principles which mirror guidelines from the Institute of Medicine and encapsulate principles from the Emanuel Framework, Nairobi Data Sharing Principles, and the COHRED guidelines. (shrink)

Existing ethics guidelines, influential literature and policies on ethical research generally focus on real-time data collection from humans. They enforce individual rights and liberties, thereby lowering need for aggregate protections. Although dependable, emerging public health research paradigms like research using public health data raise new challenges to their application. Unlike traditional research, RUPD is population-based, aligned to public health activities, and often reliant on pre-collected longitudinal data. These characteristics, when considered in relation to the generally lower protective ethico-legal frameworks of (...) the Global South, including Africa, highlight ethical gaps. Health and demographic surveillance systems are examples of public health programs that accommodate RUPD in these contexts. We set out to explore the perspectives of professionals with a working knowledge of these systems to determine practical ways of appropriating the foundational principles of health research to advance the ever growing opportunities in RUPD. We present their perspectives and in relation to the literature and our ethical analysis, make context relevant recommendations. We further argue for the development of a framework founded on the discussions and recommendations as a minimum base for achieving optimal ethics for optimal RUPD in the Global South. (shrink)

Data-sharing is a desired default in the field of public health and a source of much ethical deliberation. Sharing data potentially contributes the largest, most efficient source of scientific data, but is fraught with contextual challenges which make stakeholders, particularly those in under-resourced contexts hesitant or slow to share. Relatively little empirical research has engaged stakeholders in discussing the issue. This study sought to explore relevant experiences, contextual, and subjective explanations around the topic to provide a rich and detailed presentation (...) of what it means to different stakeholders and contexts to share data and how that can guide practice and ethical guidance. A qualitative design involving interviews was undertaken with professionals working in public health institutions endowed with data, ethics committees, and advisory agencies which help shape health research in Africa. A descriptive form of thematic analysis was used to summarize results into six key themes: The role of HDSSs in research using public health data and data-sharing; Ownership and funding are critical factors influencing data-sharing; Other factors discourage data-sharing; Promoting and sustaining data-sharing; Ethical guidance structures; and Establishing effective guidance. The themes reveal factors regarding the willingness or not to share and an intricate ethical system that current discourse could reflect. Many of the concerns resonate with the literature, but a whole other gamut of people and process issues; commitments, investments, careers, and the right ethical guidance are needed to realize a sustainable goal of reaching ‘share’ as a default. (shrink)